# Revisions:
# June 18, 2002: Explore using Gamma(1,1) prior for lambda_k.
#  Nov. 9, 2001: standardize etas so that lung cancer doesn't drive all the maps.
#  Nov. 12, 2001: incorporate both prevention & outcome into one model (so don't have to change inits & rerun)
#          Also, add code to look at ranks.
# Dec. 6, 2001: reverse incidence & mortality weights for crc in the prevention-emphasis scheme

# if you want hard-coded isigsq, 
#    comment out the lines where bcisigsq[1-4] are drawn from Gamma distributions.
#    uncomment the lines where they are set.
#    remove initialization of bcisigsq (etc) from the inits lists (for the 3 chains)
#  REMEMBER: I never used hard-coded values for isigsq for crc or lc; just for bc.
# if you want isigsq to be drawn from a prior distribution,
#    uncomment the lines where bcisigsq[1-4] are drawn from Gamma distributions.
#    comment out the lines where they are set.
#    be sure to set isiga and isigb in the data section -- they are the parameters for the Gamma distribution.

# Include the following:  (In each case, discard first 5k samples, save summary of next 5k samples)
#   Seed: 2236  Runs for random sigma, random lambda, standard units:
#      bc: all rates per 100k, percentages in [0,100] -- graphs, standardized and not stdized. 
#           (i.e. in the various arrays, the first values are: 
#                 bcincidencerate(128.2),bcmortalityrate(18.3),bcstagingpct(31.82),bcmamnotpct(21.74)
#           Gamma(.01,.01) priors on each of the sigma^2's and lambda's
###      -- so for this setup, want to record these variables

######## pbcetaun -- bcp_un1_jun18.txt (row 2 of FIg 2)
######## pbcetast -- bcp_st1_jun18.txt (row 2 of Fig 2) (and in Fig 3)
######## obcetast -- bco_st1_jun18.txt (Fig 5)

######## pcrcetast -- crcp_st1_jun18.txt, (Fig 3)
######## ocrcetast -- crco_st1_jun18.txt, (Fig 5)

######## plcetast --  lcp_st1_jun18.txt, (Fig 3)
######## olcetast --  lco_st1_jun18.txt, (Fig 5)

######## petafinal --  allp_jun18.txt (Fig 3)
######## oetafinal --  allo_jun18.txt (Fig 5)

# Seed: 93845.  same units as above; Gamma(4,0.2) priors on lambdas;
#### pbcetast -->  bcp_st4_jun19.txt  --> bcp_gam42_bw.ps
#### plcetast  --> lcp_st4_jun19.txt    --> lcp_gam42_bw.ps
#### pcrcetast --> crcp_st4_jun19.txt --> crcp_gam42_bw.ps
#### petafinal --> allp_st4_jun19.txt  --> allp_gam42_bw.ps

## Seed: 321233   Random sigma, random lambda, emphasize incidence: (Row 3 of Figure 2)
#   bc: incidence per 1,000k, mortality/1000, percents in [0,1] -- graphs, stdized & not stdized. 
#      (i.e. earlier incidence rate * 10 and mortality rate / 100  and screen,staging divided by 100)
#                 bcincidencerate(1282),bcmortalityrate(.183),bcstagingpct(.3182),bcmamnotpct(.2174)
#           Gamma(.01,.01) priors on each of the sigma^2's and lambda's
###    -- so for this setup, want to record the variables:

######## pbcetast -- bcp_st2_jun18.txt (3rd row of Fig 2)
######## pbcetaun -- bcp_un2_jun18.txt (3rd row of Fig 2)

#  Seed: 502050   Sigma fixed, lambda random, standard units for input vars (Figure 2, top row)
#    i.e.  staging/screening rates/100k, %'s in [0,100].   Gamma(.01,.01) priors for lambda, isigma^2.

### So for this setup, record the following variables:
########  pbcetaun --  bcp_un3_jun18.txt  (Fig 2, left column)
########  pbcetast -- bcp_st3_jun18.txt  (Fig 2, right column)

#   Generate 12 prevention maps, for bc only: (components of Figure 2)
#     bcp_un1_rwb.ps & bcp_un1_bw.ps ( sigma fixed,   red/white/blue or black/white )(unstandardized)
#     bcp_st1_rwb.ps & bcp_st1_bw.ps ( sigma fixed,   red/white/blue or black/white )(standardized)
#     bcp_un2_rwb.ps & bcp_un2_bw.ps ( sigma random, std wts,   red/white/blue or black/white )(unstandardized)
#     bcp_st2_rwb.ps & bcp_st2_bw.ps ( sigma random, std wts,   red/white/blue or black/white )(standardized)
#     bcp_un3_rwb.ps & bcp_un3_bw.ps ( sigma random, empasize incid.,   red/white/blue or black/white )(unstandardized)
#     bcp_st3_rwb.ps & bcp_st3_bw.ps ( sigma random, empasize incid.,   red/white/blue or black/white )(standardized)

#   Generate 4 prevention maps, one for each cancer type, plus combine the three.
#     bcp_rwb.ps, lcp_rwb.ps, crcp_rwb.ps, allp_rwb.ps, sim. for bw instead of rwb.

#   Generate 4 outcome maps, one for each cancer type, plus combine the three.
#     bco_rwb.ps, lco_rwb.ps, crco_rwb.ps, allo_rwb.ps, sim. for bw instead of rwb.

# variable and file naming conventions:
#    "bc" for Breast Cancer, "lc" for Lung Cancer, "crc" for Colorectal Cancer.
#    "p" stands for prevention weighting, "o" for outcome weighting.
#   "st" if standardizing gibbs samples, "un" if not standardizing.
#   e.g.   lcp_something means Lung Cancer, using Prevention Weighting.

model
{
isigaa <- isiga
isigbb <- isigb

 ###############################
 #####  BREAST CANCER VARS #####
 ###############################

########## Breast cancer mortality ##############
   bctheta1[1:regions] ~ car.normal(adj[],weights[],num[],bclambda[1])
#bcisigsq[1] <- 0.15
bcisigsq[1] ~ dgamma(isiga,isigb)
  bclambda[1] ~ dgamma(ilama,ilamb)
  bcsig[1] <- 1/sqrt(bcisigsq[1])
  bcmu[1] ~ dflat()
############ Breast cancer incidence ############
  bctheta2[1:regions] ~ car.normal(adj[],weights[],num[],bclambda[2])
# bcisigsq[2] <- .01 
bcisigsq[2] ~ dgamma(isiga,isigb)
  bclambda[2] ~ dgamma(ilama,ilamb)
  bcsig[2] <- 1/sqrt(bcisigsq[2])
  bcmu[2] ~ dflat()
############# Breast cancer staging ############
  bctheta3[1:regions] ~ car.normal(adj[],weights[],num[],bclambda[3])
#bcisigsq[3] <- 0.002
bcisigsq[3] ~ dgamma(isiga,isigb)
  bclambda[3] ~ dgamma(ilama,ilamb)
  bcsig[3] <- 1/sqrt(bcisigsq[3])
  bcmu[3] ~ dflat()
############## Breast cancer screening ##########
  bctheta4[1:regions] ~ car.normal(adj[],weights[],num[],bclambda[4])
#bcisigsq[4] <- .003
bcisigsq[4] ~ dgamma(isiga,isigb)
  bclambda[4] ~ dgamma(ilama,ilamb)
  bcsig[4] <- 1/sqrt(bcisigsq[4])
  bcmu[4] ~ dflat()
########## Breast cancer ##############
  for (i in 1:regions) {
    bcprecis[1,i] <- bcisigsq[1]*bcdeaths[i]/bcmortalityrate[i]
    bcmeen[1,i] <- bcmu[1] + bctheta1[i]
    bcmortalityrate[i] ~ dnorm( bcmeen[1,i], bcprecis[1,i])

    bcprecis[2,i] <- bcisigsq[2]*bcincidence[i]/bcincidencerate[i]
    bcmeen[2,i] <- bcmu[2] + bctheta2[i]
    bcincidencerate[i] ~ dnorm( bcmeen[2,i], bcprecis[2,i])

    bcprecis[3,i] <- bcisigsq[3]*bcstagingtot[i]
    bcmeen[3,i] <- bcmu[3] + bctheta3[i]
    bcstagingpct[i] ~ dnorm( bcmeen[3,i], bcprecis[3,i])

    bcprecis[4,i] <- bcisigsq[4]*bcmamtot[i]
    bcmeen[4,i] <- bcmu[4] + bctheta4[i]
    bcmamnotpct[i] ~ dnorm( bcmeen[4,i], bcprecis[4,i])
  }
  #### standardize the Gibbs sample for breast cancer:  ####
  for (i in 1:4) {
    bcmeana[i] <- mean( bcmeen[i,] )
    bcstda[i] <- sd( bcmeen[i,] )
  }
  for (i in 1:regions) {
    for (k in 1:4) {
      bcmean[k,i] <- (bcmeen[k,i] - bcmeana[k]) /bcstda[k]
    }
 }

  ### Combine 4 measures for breast cancer, standardized and non-standardized: ###
  for (i in 1:regions) {
    # eta_un(standardized) and eta_st(andardized)
    pbcetaun[i] <- pbcmortwt*bcmeen[1,i] + pbcincwt*bcmeen[2,i] + pbcstagingwt*bcmeen[3,i] + pbcscreenwt*bcmeen[4,i]
    pbcetast[i]  <- pbcmortwt*bcmean[1,i] + pbcincwt*bcmean[2,i] + pbcstagingwt*bcmean[3,i] + pbcscreenwt*bcmean[4,i]
    obcetaun[i] <- obcmortwt*bcmeen[1,i] + obcincwt*bcmeen[2,i] + obcstagingwt*bcmeen[3,i] + obcscreenwt*bcmeen[4,i]
    obcetast[i]  <- obcmortwt*bcmean[1,i] + obcincwt*bcmean[2,i] + obcstagingwt*bcmean[3,i] + obcscreenwt*bcmean[4,i]
  }

#  bcStLouis <- rank( pbcetast[],69 )
#  bcHenn <- rank( pbcetast[],27 )
#  bcRock <- rank( pbcetast[],67)
#  bcKoochiching <- rank( pbcetast[],36 )

  #### Code for tracking rank of various counties, for breast cancer: ###
  bcStLouis1 <- rank( bcmean[1,],69 )
  bcHenn1 <- rank( bcmean[1,],27 )
  bcRock1 <- rank( bcmean[1,],67)
  bcKoochiching1 <- rank( bcmean[1,],36 )

  bcStLouis2 <- rank( bcmean[2,],69 )
  bcHenn2 <- rank( bcmean[2,],27 )
  bcRock2 <- rank( bcmean[2,],67)
  bcKoochiching2 <- rank( bcmean[2,],36 )

  bcStLouis3 <- rank( bcmean[3,],69 )
  bcHenn3 <- rank( bcmean[3,],27 )
  bcRock3 <- rank( bcmean[3,],67)
  bcKoochiching3 <- rank( bcmean[3,],36 )

  bcStLouis4 <- rank( bcmean[4,],69 )
  bcHenn4 <- rank( bcmean[4,],27 )
  bcRock4 <- rank( bcmean[4,],67)
  bcKoochiching4 <- rank( bcmean[4,],36 )

 ####################################
 #####  COLORECTAL CANCER VARS #####
 ####################################

    crctheta1[1:regions] ~ car.normal(adj[],weights[],num[],crclambda[1])
    crclambda[1] ~ dgamma(ilama,ilamb)
    crcisigsq[1] ~ dgamma(isiga,isigb)
    crcsig[1] <- 1/sqrt(crcisigsq[1])
    crcmu[1] ~ dflat()

    crctheta2[1:regions] ~ car.normal(adj[],weights[],num[],crclambda[2])
    crclambda[2] ~ dgamma(ilama,ilamb)
    crcisigsq[2] ~ dgamma(isiga,isigb)
    crcsig[2] <- 1/sqrt(crcisigsq[2])
    crcmu[2] ~ dflat()

    crctheta3[1:regions] ~ car.normal(adj[],weights[],num[],crclambda[3])
    crclambda[3] ~ dgamma(ilama,ilamb)
    crcisigsq[3] ~ dgamma(isiga,isigb)
    crcsig[3] <- 1/sqrt(crcisigsq[3])
    crcmu[3] ~ dflat()

    crctheta4[1:regions] ~ car.normal(adj[],weights[],num[],crclambda[4])
    crclambda[4] ~ dgamma(ilama,ilamb)
    crcisigsq[4] ~ dgamma(isiga,isigb)
    crcsig[4] <- 1/sqrt(crcisigsq[4])
    crcmu[4] ~ dflat()

  for (i in 1:regions) {
    crcprecis[1,i] <- crcisigsq[1]*crcdobs[i]/crcdrate[i]
    crcmeen[1,i] <- crcmu[1] + crctheta1[i]
    crcdrate[i] ~ dnorm( crcmeen[1,i], crcprecis[1,i])

    crcprecis[2,i] <- crcisigsq[2]*crciobs[i]/crcirate[i]
    crcmeen[2,i] <- crcmu[2] + crctheta2[i]
    crcirate[i] ~ dnorm( crcmeen[2,i],crcprecis[2,i])

    crcprecis[3,i] <- crcisigsq[3]*crcstagn[i]
    crcmeen[3,i] <- crcmu[3] + crctheta3[i]
    crcstagingpct[i] ~ dnorm( crcmeen[3,i], crcprecis[3,i])

    crcprecis[4,i] <- crcisigsq[4]*crcscreen[i]
    crcmeen[4,i] <- crcmu[4] + crctheta4[i]
    crcnotscreenpct[i] ~ dnorm( crcmeen[4,i], crcprecis[4,i])

     crceta[i] <- (crcmeen[1,i] + crcmeen[2,i])/4 + (crcmeen[3,i]+crcmeen[4,i])/4
  }

  for (i in 1:4) {
    crcmeana[i] <- mean( crcmeen[i,] )
    crcstda[i] <- sd( crcmeen[i,] )
  }
  for (i in 1:regions) {
    for (k in 1:4) {
      crcmean[k,i] <- (crcmeen[k,i] - crcmeana[k]) /crcstda[k]
    }
 }
  for (i in 1:regions) {
    # eta_un(standardized) and eta_st(andardized)
#    pcrcetaun[i] <- pcrcmortwt*crcmeen[1,i] + pcrcincwt*crcmeen[2,i] + pcrcstagingwt*crcmeen[3,i] + pcrcscreenwt*crcmeen[4,i]
    pcrcetast[i]    <- pcrcmortwt*crcmean[1,i] + pcrcincwt*crcmean[2,i] + pcrcstagingwt*crcmean[3,i] + pcrcscreenwt*crcmean[4,i]
#    ocrcetaun[i] <- ocrcmortwt*crcmeen[1,i] + ocrcincwt*crcmeen[2,i] + ocrcstagingwt*crcmeen[3,i] + ocrcscreenwt*crcmeen[4,i]
    ocrcetast[i]    <- ocrcmortwt*crcmean[1,i] + ocrcincwt*crcmean[2,i] + ocrcstagingwt*crcmean[3,i] + ocrcscreenwt*crcmean[4,i]
  }

#  crcStLouis <- rank( pcrcetast[],69 )
#  crcHenn <- rank( pcrcetast[],27 )
#  crcRock <- rank( pcrcetast[],67)
#  crcKoochiching <- rank( pcrcetast[],36 )

  crcStLouis1 <- rank( crcmean[1,],69 )
  crcHenn1 <- rank( crcmean[1,],27 )
  crcRock1 <- rank( crcmean[1,],67)
  crcKoochiching1 <- rank( crcmean[1,],36 )

  crcStLouis2 <- rank( crcmean[2,],69 )
  crcHenn2 <- rank( crcmean[2,],27 )
  crcRock2 <- rank( crcmean[2,],67)
  crcKoochiching2 <- rank( crcmean[2,],36 )

  crcStLouis3 <- rank( crcmean[3,],69 )
  crcHenn3 <- rank( crcmean[3,],27 )
  crcRock3 <- rank( crcmean[3,],67)
  crcKoochiching3 <- rank( crcmean[3,],36 )

  crcStLouis4 <- rank( crcmean[4,],69 )
  crcHenn4 <- rank( crcmean[4,],27 )
  crcRock4 <- rank( crcmean[4,],67)
  crcKoochiching4 <- rank( crcmean[4,],36 )

 ####################################
 #########  LUNG CANCER VARS ########
 ####################################

  lctheta1[1:regions] ~ car.normal(adj[],weights[],num[],lclambda[1])
  lclambda[1] ~ dgamma(ilama,ilamb)
  lcisigsq[1] ~ dgamma(isiga,isigb)
  lcsig[1] <- 1/sqrt(lcisigsq[1])
  lcmu[1] ~ dflat()

  lctheta2[1:regions] ~ car.normal(adj[],weights[],num[],lclambda[2])
  lclambda[2] ~ dgamma(ilama,ilamb)
  lcisigsq[2] ~ dgamma(isiga,isigb)
  lcsig[2] <- 1/sqrt(lcisigsq[2])
  lcmu[2] ~ dflat()

  lctheta3[1:regions] ~ car.normal(adj[],weights[],num[],lclambda[3])
  lclambda[3] ~ dgamma(ilama,ilamb)
  lcisigsq[3] ~ dgamma(isiga,isigb)
  lcsig[3] <- 1/sqrt(lcisigsq[3])
  lcmu[3] ~ dflat()

  for (i in 1:regions) {
    lcprecis[1,i] <- lcisigsq[1]*lcdobs[i]/lcdrate[i]
    lcmeen[1,i] <- lcmu[1] + lctheta1[i]
    lcdrate[i] ~ dnorm( lcmeen[1,i], lcprecis[1,i])

    lcprecis[2,i] <- lcisigsq[2]*lciobs[i]/lcirate[i]
    lcmeen[2,i] <- lcmu[2] + lctheta2[i]
    lcirate[i] ~ dnorm( lcmeen[2,i], lcprecis[2,i])

    lcprecis[3,i] <- lcisigsq[3]*lcscreen[i]
    lcmeen[3,i] <- lcmu[3] + lctheta3[i]
    lccursmkpct[i] ~ dnorm( lcmeen[3,i], lcprecis[3,i])
  }

  for (i in 1:3) {
    lcmeana[i] <- mean( lcmeen[i,] )
    lcstda[i] <- sd( lcmeen[i,] )
  }
  for (i in 1:regions) {
    for (k in 1:3) {
      lcmean[k,i] <- (lcmeen[k,i] - lcmeana[k]) / lcstda[k]
    }
 }
  
 for (i in 1:regions) {
    plcetast[i]  <- plcmortwt*lcmean[1,i] + plcincwt*lcmean[2,i] + plccursmkwt*lcmean[3,i] 
    olcetast[i]  <- olcmortwt*lcmean[1,i] + olcincwt*lcmean[2,i] + olccursmkwt*lcmean[3,i] 
 }

#  lcStLouis <- rank( plcetast[],69 )
#  lcHenn <- rank( plcetast[],27 )
#  lcRock <- rank( plcetast[],67)
#  lcKoochiching <- rank( plcetast[],36 )

#  lcStLouis1 <- rank( lcmean[1,],69 )
#  lcHenn1 <- rank( lcmean[1,],27 )
#  lcRock1 <- rank( lcmean[1,],67)
#  lcKoochiching1 <- rank( lcmean[1,],36 )

#  lcStLouis2 <- rank( lcmean[2,],69 )
#  lcHenn2 <- rank( lcmean[2,],27 )
#  lcRock2 <- rank( lcmean[2,],67)
#  lcKoochiching2 <- rank( lcmean[2,],36 )

#  lcStLouis3 <- rank( lcmean[3,],69 )
#  lcHenn3 <- rank( lcmean[3,],27 )
#  lcRock3 <- rank( lcmean[3,],67)
#  lcKoochiching3 <- rank( lcmean[3,],36 )

########### standardize again, before coming up with etafinal: ####
#    pbcmean2 <- mean( pbcetast[] )
#   pcrcmean2 <- mean( pcrcetast[] )
#   plcmean2 <- mean( plcetast[] )

#    pbcsd2 <- sd( pbcetast[] )
#    pcrcsd2 <- sd( pcrcetast[] )
#    plcsd2 <- sd( plcetast[] )

#    obcmean2 <- mean( obcetast[] )
#    ocrcmean2 <- mean( ocrcetast[] )
#    olcmean2 <- mean( olcetast[] )

#    obcsd2 <- sd( obcetast[] )
#    ocrcsd2 <- sd( ocrcetast[] )
#    olcsd2 <- sd( olcetast[] )

#    for (i in 1:regions) {
 #     pbcave2[i]    <- (pbcetast[i] - pbcmean2) / pbcsd2
  #    pcrcave2[i]   <- (pcrcetast[i] - pcrcmean2) / pcrcsd2
   #   plcave2[i]     <- (plcetast[i] - plcmean2) / plcsd2

#      obcave2[i]    <- (obcetast[i] - obcmean2) / obcsd2
 #     ocrcave2[i]   <- (ocrcetast[i] - ocrcmean2) / ocrcsd2
  #    olcave2[i]     <- (olcetast[i] - olcmean2) / olcsd2
   # }
########### end of 2nd standardization  ###############################
##### (2nd standardization commented out b/c it didn't change anything...) #####

  #######################################
  ####### Combine the 3 cancer types  ########
  ####### Standardized & non-standardized ####
  #######################################

    for (i in 1:regions) {
       petafinal[i] <- (pbcetast[i] + pcrcetast[i] + plcetast[i])/3
       oetafinal[i] <- (obcetast[i] + ocrcetast[i] + olcetast[i])/3
       #      petafinal2[i] <- (pbcave2[i] + pcrcave2[i] + plcave2[i])/3
       #     oetafinal2[i] <- (obcave2[i] + ocrcave2[i] + olcave2[i])/3
    }
}               ################ End of Model ################

# WInBUGS gamma convention: E = alpha/lambda, V = alpha/lambda^2

# bcmortalityrate = mortality / 100k
# bcincidencerate = incidence / 100k
# bcstagingpct = % diagnosed at late stage
# bcmamnotpct = % who didn't get screened
bcisigsq=c(.15,.01,.002,.003), 
===============================================================

###################################
# Initializations:  chain 1:
###################################
list(
bcisigsq=c(.15,.01,.002,.003), 
crcisigsq=c(.01,.01,.01,.01),   lcisigsq=c(.01,.01,.01), 

bclambda=c(1,1,1,1), bcmu=c(0,0,0,0),
 bctheta1=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
 bctheta2=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
  bctheta3=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
 bctheta4=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0) ,

crclambda=c(1,1,1,1), crcmu=c(0,0,0,0),
 crctheta1=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
 crctheta2=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
  crctheta3=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
 crctheta4=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0) ,

lclambda=c(1,1,1), 
lcmu=c(0,0,0),
 lctheta1=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
 lctheta2=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0),
 lctheta3=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0) 
)

#bcisigsq=c(.15,.01,.002,.003),   crcisigsq=c(.01,.01,.01,.01),   lcisigsq=c(.01,.01,.01), 
# This list is for checking convergence, e.g. via G-R statistic:
###################################
# Initializations:  chain 2:
###################################
list(
bcisigsq=c(.10,.001,.001,.001),   crcisigsq=c(.005,.005,.005,.005),   lcisigsq=c(.005,.005,.005), 

bclambda=c(66,44,11,55),bcmu=c(10,20,30,40),
bctheta1=c(7,7,7,7,7,7,7,7,7,7, 7,7,7,7,7,7,7,7,7,7,
7,7,7,7,7,7,7,7,7,7, 7,7,7,7,7,7,7,7,7,7,  7,7,7,7,7,7,7,7,7,7, 7,7,7,7,7,7,7,7,7,7,
7,7,7,7,7,7,7,7,7,7, 7,7,7,7,7,7,7,7,7,7,  7,7,7,7,7,7,7),
bctheta2=c(5,5,5,5,5,5,5,5,5,5, 5,5,5,5,5,5,5,5,5,5,
5,5,5,5,5,5,5,5,5,5, 5,5,5,5,5,5,5,5,5,5,  5,5,5,5,5,5,5,5,5,5, 5,5,5,5,5,5,5,5,5,5,
5,5,5,5,5,5,5,5,5,5, 5,5,5,5,5,5,5,5,5,5,  5,5,5,5,5,5,5),
bctheta3=c(3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,  3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,  3,3,3,3,3,3,3),
bctheta4=c(9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,
9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,  9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,
9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,  9,9,9,9,9,9,9),

crclambda=c(66,44,11,55),crcmu=c(10,20,30,40),
 crctheta1=c(
10,10,10,10,10,10,10,10,10,10, 10,10,10,10,10,10,10,10,10,10, 10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10,10,10),
crctheta2=c(3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3,3),
crctheta3=c(5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,
5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,
5,5,5,5,5,5,5,5,5,5,5),
crctheta4=c(7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,
7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,
7,7,7,7,7,7,7,7,7,7,7),

lclambda=c(66,44,11),lcmu=c(10,20,30),
 lctheta1=c(2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,
2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,
2,2,2,2,2,2,2,2,2,2,2),
lctheta2=c(4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,
4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,
4,4,4,4,4,4,4,4,4,4,4),
lctheta3=c(6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,
6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,
6,6,6,6,6,6,6,6,6,6,6)
)

#bcisigsq=c(.15,.01,.002,.003),   crcisigsq=c(.01,.01,.01,.01),   lcisigsq=c(.01,.01,.01), 
###################################
# Initializations:  chain 3:
###################################
list(
bcisigsq=c(.3,.1,.02,.03),   crcisigsq=c(.05,.05,.05,.05),   lcisigsq=c(.05,.05,.05), 

bclambda=c(55,66,44,11),bcmu=c(40,10,20,30),
bctheta1=c(3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,  3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3, 3,3,3,3,3,3,3,3,3,3,  3,3,3,3,3,3,3),
bctheta2=c(1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,  1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,  1,1,1,1,1,1,1),
bctheta3=c(8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,
8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,  8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,
8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,  8,8,8,8,8,8,8),
bctheta4=c(10,10,10,10,10,10,10,10,10,10, 10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10, 10,10,10,10,10,10,10,10,10,10,  10,10,10,10,10,10,10,10,10,10, 10,10,10,10,10,10,10,10,10,10,
10,10,10,10,10,10,10,10,10,10, 10,10,10,10,10,10,10,10,10,10,  10,10,10,10,10,10,10),

crclambda=c(55,66,44,11),crcmu=c(40,10,20,30),
 crctheta1=c(8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,
8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,
8,8,8,8,8,8,8,8,8,8,8),
 crctheta2=c(2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,
2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,
2,2,2,2,2,2,2,2,2,2,2),
 crctheta3=c(4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,
4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,
4,4,4,4,4,4,4,4,4,4,4),
 crctheta4=c(3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,
3,3,3,3,3,3,3,3,3,3,3),

lclambda=c(55,66,44),lcmu=c(40,10,20),
 lctheta1=c(7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,
7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,
7,7,7,7,7,7,7,7,7,7,7),
 lctheta2=c(6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,
6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,
6,6,6,6,6,6,6,6,6,6,6),
 lctheta3=c(9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,
9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,
9,9,9,9,9,9,9,9,9,9,9)
)
#===============================================================

# Use these numbers for "usual" rates:
#     Rates for mortality and incidence are cases /100k, 
#     Screening and staging figures are expressed as percents, 0-100.

bcincidencerate=c(128.2, 93.7, 108.3, 88.8, 88.5, 129.2, 105.3, 96.2, 104.1, 92,
129.3, 97.3, 103, 98.7, 114.1, 91.2, 111.4, 112.3, 119.2, 96.2, 96,
74.7, 85.9, 93.3, 110.2, 144.4, 122.9, 104.3, 111.1, 107.9, 115.3,
77.1, 81.3, 125.1, 81.6, 114.3, 82.7, 130.3, 118.6, 121.4, 73.4,
94.6, 120.6, 98.5, 107.9, 104, 90.1, 86.8, 95.7, 99.1, 84.6, 92.7,
95.8, 72.5, 129.7, 107.8, 131.5, 103.7, 128.7, 107.7, 90.2, 116.1,
65.4, 103.4, 89, 111.4, 116.4, 110.8, 105.9, 97.7, 127.6, 123.4,
110.1, 120.3, 85.8, 125.2, 78.2, 105.3, 106.6, 148, 110.5, 121.9,
95, 103.6, 110.4, 92.9, 85.4),

bcmortalityrate=c(18.3, 21.7, 21.1, 18.5, 18.7, 29.4, 23.5, 17.5, 11, 14.7, 22.4,
21.6, 20.7, 20.9, 39.8, 14.6, 26.1, 28.6, 23.7, 25.1, 20.9, 26.1,
23.7, 25.1, 35.2, 36.3, 25.9, 26.3, 21.8, 28.6, 26.8, 31.3, 10.7,
28.3, 31.8, 21.5, 14.3, 22.7, 20.5, 31.6, 52.7, 27.1, 21.4, 32.8,
12, 27.1, 32.5, 26.6, 22, 22, 12.7, 17.1, 16.6, 20, 25.1, 21.4,
23.3, 19.4, 37.5, 17.7, 16.6, 22.9, 8.1, 22.2, 20.3, 26.2, 29.2,
24.5, 21.6, 27.5, 25.1, 42.8, 21.3, 23.3, 26.5, 24.1, 16.9, 37.2,
19.1, 31, 21.8, 22.6, 27.6, 20.6, 15.5, 22.1, 20.3),

bcmamnotpct = c(
21.74,8.66,30.30,27.27,18.75,25.00,13.46,18.18,14.29,16.67,17.86,0.00,
30.00,11.36,0.00,0.00,15.79,18.75,9.66,14.29,20.59,19.05,11.54,16.67,
21.74,14.29,12.76,15.79,22.22,20.00,17.54,20.00,21.05,28.57,40.00,0.00,
42.86,8.33,50.00,21.43,12.50,34.78,20.00,20.00,25.00,24.00,12.00,22.73,
23.08,12.82,16.67,0.00,28.00,16.67,16.33,20.75,0.00,16.67,14.29,24.39,
20.00,12.91,0.00,17.24,14.29,5.56,21.05,15.38,14.68,16.67,9.09,30.77,
18.60,21.43,27.27,33.33,36.36,0.00,18.18,16.00,7.14,15.65,0.00,50.00,
9.30,16.67,20.00),

bcstagingpct=c(31.82, 26.89, 35.21, 29.51, 32.08, 7.69, 26.23, 32.26, 19.23,
29.47, 34.62, 21.62, 29.55, 27.27, 42.11, 25, 25.64, 27.74, 27.07,
38.71, 28.79, 29.27, 23.91, 25.32, 33.03, 19.23, 26.26, 22.73,
22.45, 37.7, 20.51, 52.63, 13.04, 26.32, 20, 25, 30.77, 34.21, 37.5,
29.09, 18.18, 18.52, 30.21, 54.55, 36.67, 27.4, 38.46, 42.55, 30,
22.55, 19.23, 30, 22.22, 37.5, 25.25, 20, 33.33, 30, 17.95, 32.97,
21.88, 26.2, 25, 23.91, 25, 34.43, 20.51, 54.17, 27.03, 20.88,
30.34, 36, 26.75, 37.8, 17.65, 41.94, 27.5, 31.25, 22.22, 31.11,
33.33, 27.78, 26.67, 42.11, 33.63, 27.56, 24.24),

# Use these numbers for emphasizing incidence:
#    Per million for incidence (i.e. multiply above figures by 10)
#    Per thousand for mortality (i.e. divide above figures by 100)
#    Staging and screening as fractions between 0 and 1 (i.e. divide above figures by 100)

bcincidencerate=c(
1282,937,1083,888,885,1292,1053,962,1041,920,1293,973,
1030,987,1141,912,1114,1123,1192,962,960,747,859,933,
1102,1444,1229,1043,1111,1079,1153,771,813,1251,816,1143,
827,1303,1186,1214,734,946,1206,985,1079,1040,901,868,
957,991,846,927,958,725,1297,1078,1315,1037,1287,1077,
902,1161,654,1034,890,1114,1164,1108,1059,977,1276,1234,
1101,1203,858,1252,782,1053,1066,1480,1105,1219,950,1036,
1104,929,854),

bcmortalityrate=c(
0.183,0.217,0.211,0.185,0.187,0.294,0.235,0.175,0.11,0.147,0.224,0.216,
0.207,0.209,0.398,0.146,0.261,0.286,0.237,0.251,0.209,0.261,0.237,0.251,
0.352,0.363,0.259,0.263,0.218,0.286,0.268,0.313,0.107,0.283,0.318,0.215,
0.143,0.227,0.205,0.316,0.527,0.271,0.214,0.328,0.12,0.271,0.325,0.266,
0.22,0.22,0.127,0.171,0.166,0.2,0.251,0.214,0.233,0.194,0.375,0.177,
0.166,0.229,0.081,0.222,0.203,0.262,0.292,0.245,0.216,0.275,0.251,0.428,
0.213,0.233,0.265,0.241,0.169,0.372,0.191,0.31,0.218,0.226,0.276,0.206,
0.155,0.221,0.203),

bcmamnotpct=c(
0.2174,0.08661,0.303,0.2727,0.1875,0.25,0.1346,0.1818,0.1429,0.1667,0.1786,0,
0.3,0.1136,0,0,0.1579,0.1875,0.09659,0.1429,0.2059,0.1905,0.1154,0.1667,
0.2174,0.1429,0.1276,0.1579,0.2222,0.2,0.1754,0.2,0.2105,0.2857,0.4,0,
0.4286,0.08333,0.5,0.2143,0.125,0.3478,0.2,0.2,0.25,0.24,0.12,0.2273,
0.2308,0.1282,0.1667,0,0.28,0.1667,0.1633,0.2075,0,0.1667,0.1429,0.2439,
0.2,0.1291,0,0.1724,0.1429,0.05556,0.2105,0.1538,0.1468,0.1667,0.09091,0.3077,
0.186,0.2143,0.2727,0.3333,0.3636,0,0.1818,0.16,0.07143,0.1565,0,0.5,
0.09302,0.1667,0.2),

bcstagingpct=c(
0.3182,0.2689,0.3521,0.2951,0.3208,0.0769,0.2623,0.3226,0.1923,0.2947,0.3462,0.2162,
0.2955,0.2727,0.4211,0.25,0.2564,0.2774,0.2707,0.3871,0.2879,0.2927,0.2391,0.2532,
0.3303,0.1923,0.2626,0.2273,0.2245,0.377,0.2051,0.5263,0.1304,0.2632,0.2,0.25,
0.3077,0.3421,0.375,0.2909,0.1818,0.1852,0.3021,0.5455,0.3667,0.274,0.3846,0.4255,
0.3,0.2255,0.1923,0.3,0.2222,0.375,0.2525,0.2,0.3333,0.3,0.1795,0.3297,
0.2188,0.262,0.25,0.2391,0.25,0.3443,0.2051,0.5417,0.2703,0.2088,0.3034,0.36,
0.2675,0.378,0.1765,0.4194,0.275,0.3125,0.2222,0.3111,0.3333,0.2778,0.2667,0.4211,
0.3363,0.2756,0.2424),

# prevention weights:
pbcscreenwt=.4, pbcstagingwt=.3, pbcmortwt=.2, pbcincwt=.1,
pcrcscreenwt=.4,pcrcstagingwt=.3, pcrcmortwt=.2, pcrcincwt=.1,
plccursmkwt=.7, plcmortwt=.15, plcincwt=.15,
# outcome weights:
obcscreenwt=.1, obcstagingwt=.3, obcmortwt=.4, obcincwt=.2,
ocrcscreenwt=.1,ocrcstagingwt=.3, ocrcmortwt=.4, ocrcincwt=.2,
olccursmkwt=.1, olcmortwt=.5, olcincwt=.4,

ilama=.01,
ilamb=.01,
ilama=1.0,
ilamb=1.0,
ilama=10,ilamb=0.5
ilama=4, ilamb=0.2  # seed 93845

#===============================================================

# Recall for WInBUGS, Gamma(alpha,beta) has mean alpha/beta and var alpha/beta^2

######################
####    Data  :  #####
######################
list(regions=87, 
isiga=.01,
isigb=.01,
ilama=4,
ilamb=.2,

pbcscreenwt=.4, pbcstagingwt=.3, pbcmortwt=.2, pbcincwt=.1,
pcrcscreenwt=.4,pcrcstagingwt=.3, pcrcmortwt=.1, pcrcincwt=.2,
plccursmkwt=.7, plcmortwt=.15, plcincwt=.15,

obcscreenwt=.1, obcstagingwt=.3, obcmortwt=.4, obcincwt=.2,
ocrcscreenwt=.1,ocrcstagingwt=.3, ocrcmortwt=.4, ocrcincwt=.2,
olccursmkwt=.1, olcmortwt=.5, olcincwt=.4,

bcincidencerate=c(128.2, 93.7, 108.3, 88.8, 88.5, 129.2, 105.3, 96.2, 104.1, 92,
129.3, 97.3, 103, 98.7, 114.1, 91.2, 111.4, 112.3, 119.2, 96.2, 96,
74.7, 85.9, 93.3, 110.2, 144.4, 122.9, 104.3, 111.1, 107.9, 115.3,
77.1, 81.3, 125.1, 81.6, 114.3, 82.7, 130.3, 118.6, 121.4, 73.4,
94.6, 120.6, 98.5, 107.9, 104, 90.1, 86.8, 95.7, 99.1, 84.6, 92.7,
95.8, 72.5, 129.7, 107.8, 131.5, 103.7, 128.7, 107.7, 90.2, 116.1,
65.4, 103.4, 89, 111.4, 116.4, 110.8, 105.9, 97.7, 127.6, 123.4,
110.1, 120.3, 85.8, 125.2, 78.2, 105.3, 106.6, 148, 110.5, 121.9,
95, 103.6, 110.4, 92.9, 85.4),

bcmortalityrate=c(18.3, 21.7, 21.1, 18.5, 18.7, 29.4, 23.5, 17.5, 11, 14.7, 22.4,
21.6, 20.7, 20.9, 39.8, 14.6, 26.1, 28.6, 23.7, 25.1, 20.9, 26.1,
23.7, 25.1, 35.2, 36.3, 25.9, 26.3, 21.8, 28.6, 26.8, 31.3, 10.7,
28.3, 31.8, 21.5, 14.3, 22.7, 20.5, 31.6, 52.7, 27.1, 21.4, 32.8,
12, 27.1, 32.5, 26.6, 22, 22, 12.7, 17.1, 16.6, 20, 25.1, 21.4,
23.3, 19.4, 37.5, 17.7, 16.6, 22.9, 8.1, 22.2, 20.3, 26.2, 29.2,
24.5, 21.6, 27.5, 25.1, 42.8, 21.3, 23.3, 26.5, 24.1, 16.9, 37.2,
19.1, 31, 21.8, 22.6, 27.6, 20.6, 15.5, 22.1, 20.3),

bcmamnotpct = c(
21.74,8.66,30.30,27.27,18.75,25.00,13.46,18.18,14.29,16.67,17.86,0.00,
30.00,11.36,0.00,0.00,15.79,18.75,9.66,14.29,20.59,19.05,11.54,16.67,
21.74,14.29,12.76,15.79,22.22,20.00,17.54,20.00,21.05,28.57,40.00,0.00,
42.86,8.33,50.00,21.43,12.50,34.78,20.00,20.00,25.00,24.00,12.00,22.73,
23.08,12.82,16.67,0.00,28.00,16.67,16.33,20.75,0.00,16.67,14.29,24.39,
20.00,12.91,0.00,17.24,14.29,5.56,21.05,15.38,14.68,16.67,9.09,30.77,
18.60,21.43,27.27,33.33,36.36,0.00,18.18,16.00,7.14,15.65,0.00,50.00,
9.30,16.67,20.00),

bcstagingpct=c(31.82, 26.89, 35.21, 29.51, 32.08, 7.69, 26.23, 32.26, 19.23,
29.47, 34.62, 21.62, 29.55, 27.27, 42.11, 25, 25.64, 27.74, 27.07,
38.71, 28.79, 29.27, 23.91, 25.32, 33.03, 19.23, 26.26, 22.73,
22.45, 37.7, 20.51, 52.63, 13.04, 26.32, 20, 25, 30.77, 34.21, 37.5,
29.09, 18.18, 18.52, 30.21, 54.55, 36.67, 27.4, 38.46, 42.55, 30,
22.55, 19.23, 30, 22.22, 37.5, 25.25, 20, 33.33, 30, 17.95, 32.97,
21.88, 26.2, 25, 23.91, 25, 34.43, 20.51, 54.17, 27.03, 20.88,
30.34, 36, 26.75, 37.8, 17.65, 41.94, 27.5, 31.25, 22.22, 31.11,
33.33, 27.78, 26.67, 42.11, 33.63, 27.56, 24.24),

bcdeaths=c(14, 134, 24, 19, 19, 8, 41, 23, 13, 26, 19, 13, 24, 37, 13, 4, 17,
55, 169, 13, 25, 22, 20, 35, 57, 11, 875, 21, 15, 22, 44, 16, 6, 41,
7, 15, 8, 11, 5, 30, 14, 25, 27, 6, 6, 22, 24, 24, 22, 42, 10, 16,
19, 10, 83, 50, 14, 16, 15, 30, 7, 390, 2, 16, 15, 41, 15, 10, 184,
43, 30, 22, 73, 25, 8, 9, 17, 8, 18, 15, 16, 93, 16, 5, 34, 44, 14),

bcincidence=c(70, 597, 102, 92, 74, 33, 162, 99, 107, 136, 116, 56, 108, 156, 31,
16, 62, 198, 850, 47, 111, 57, 71, 118, 152, 37, 3846, 71, 66, 82,
172, 33, 37, 169, 22, 60, 36, 55, 19, 96, 24, 78, 125, 15, 43, 95,
68, 63, 102, 156, 36, 70, 79, 25, 399, 232, 59, 75, 53, 128, 46,
1737, 11, 70, 62, 159, 54, 47, 784, 154, 138, 63, 354, 122, 31, 51,
67, 22, 70, 72, 73, 498, 43, 29, 167, 181, 44),

bcstagingtot=c(44, 450, 71, 61, 53, 26, 122, 62, 78, 95, 78, 37, 88, 99, 19, 8,
39, 137, 628, 31, 66, 41, 46, 79, 109, 26, 2749, 44, 49, 61, 117,
19, 23, 114, 15, 40, 26, 38, 8, 55, 11, 54, 96, 11, 30, 73, 52, 47,
60, 102, 26, 50, 54, 16, 301, 165, 42, 50, 39, 91, 32, 1252, 8, 46,
48, 122, 39, 24, 529, 91, 89, 50, 243, 82, 17, 31, 40, 16, 45, 45,
48, 360, 30, 19, 113, 127, 33),

bcmamtot=c(23, 127, 33, 22, 32, 12, 52, 22, 21, 24, 28, 17, 20, 44, 8, 5, 19,
48, 176, 14, 34, 21, 26, 42, 46, 7, 807, 19, 18, 15, 57, 10, 19, 42,
10, 9, 7, 12, 2, 28, 8, 23, 25, 5, 8, 25, 25, 22, 39, 39, 6, 16, 25,
12, 98, 53, 17, 18, 14, 41, 15, 426, 2, 29, 14, 36, 19, 13, 218, 36,
22, 13, 86, 28, 11, 9, 11, 1, 11, 25, 14, 115, 7, 2, 43, 54, 5),

crcdrate=c(22.4, 12.3, 19.3, 20.9, 13.4, 24.1, 14.4, 18.7, 14.4, 20.6, 12.9,
15.3, 16.7, 14.0, 13.2, 6.4, 13.6, 15.4, 14.5, 11.9, 16.1, 17.4,
17.5, 14.7, 15.8, 21.4, 14.3, 14.0, 15.6, 9.9, 21.7, 13.7, 21.6,
15.0, 9.2, 11.7, 16.7, 15.7, 3.0, 13.7, 35.1, 10.9, 14.2, 19.6,
14.1, 19.6, 12.7, 16.8, 15.6, 20.7, 9.9, 13.0, 12.8, 25.8, 14.1,
16.6, 15.0, 17.5, 18.9, 19.7, 17.3, 15.5, 13.2, 20.6, 13.0, 17.7,
13.8, 12.7, 15.1, 17.3, 19.1, 25.8, 12.9, 18.7, 20.2, 19.5, 13.3,
16.4, 15.8, 22.3, 10.8, 17.3, 21.0, 21.6, 19.0, 13.5, 26.2),

crcirate=c(50.5, 36.5, 46.7, 45.3, 52.8, 64.6, 46.9, 47.7, 43.4, 46.3, 45.2,
40.3, 54.2, 42.9, 52.6, 32.4, 51.3, 34.8, 45.1, 44.8, 44.0, 40.9,
41.3, 40.1, 36.3, 67.4, 40.4, 50.6, 44.6, 32.7, 55.5, 37.7, 37.4,
38.1, 45.3, 35.1, 43.8, 43.7, 34.8, 38.9, 56.8, 44.3, 41.5, 50.0,
53.5, 51.7, 43.4, 42.2, 46.9, 67.0, 39.3, 38.9, 39.7, 46.2, 44.8,
49.6, 50.0, 48.9, 36.1, 49.9, 47.6, 39.2, 38.4, 47.6, 39.1, 39.4,
30.7, 41.7, 45.1, 41.6, 54.8, 53.2, 38.3, 38.5, 56.6, 67.3, 36.3,
53.8, 47.4, 52.5, 39.7, 43.1, 61.8, 63.7, 48.1, 42.9, 60.9),

crcstagingpct=c(45.24, 52.98, 33.33, 71.93, 56.86, 57.69, 59.38, 57.38, 51.43,
58.90, 55.88, 78.79, 52.46, 47.01, 63.64, 70.00, 52.38, 58.14,
56.64, 66.67, 61.76, 78.26, 57.45, 56.92, 65.22, 59.09, 60.62,
40.48, 39.53, 52.94, 47.66, 50.00, 60.00, 61.11, 75.00, 64.52,
68.42, 46.15, 81.82, 50.00, 58.62, 63.64, 63.16, 55.56, 65.71,
66.15, 56.00, 50.00, 54.79, 47.65, 73.68, 57.58, 52.17, 61.90,
64.63, 51.23, 44.74, 51.02, 60.00, 66.22, 51.22, 57.14, 50.00,
75.00, 73.68, 60.26, 72.22, 54.55, 52.06, 55.84, 70.42, 50.00,
52.98, 50.85, 59.26, 64.10, 51.16, 40.00, 72.22, 62.22, 50.00,
51.79, 68.29, 58.33, 62.77, 58.33, 42.22),

crcnotscreenpct = c(
76.67,55.25,73.17,65.38,44.83,61.54,69.64,54.17,69.57,60.00,
72.00,61.11,56.52,47.17,50.00,33.33,76.92,63.24,47.85,66.67,
69.44,50.00,57.58,78.00,66.67,83.33,54.29,65.22,83.33,60.00,
60.94,55.56,77.27,59.57,100.00,80.00,80.00,50.00,100.00,67.74,
57.14,56.00,69.44,66.67,41.67,63.64,50.00,70.00,62.79,54.55,
66.67,57.89,76.92,66.67,53.27,72.73,78.57,56.52,91.67,75.00,
90.00,54.45,100.00,69.23,64.71,63.41,60.00,75.00,69.01,52.08,
62.50,66.67,60.00,70.27,50.00,90.00,68.42,100.00,71.43,68.75,
63.64,55.81,62.50,100.00,65.52,67.44,100.00),

crcdobs=c(27, 131, 41, 46, 27, 17, 53, 42, 32, 52, 29, 22, 34, 48, 11, 2, 19,
62, 176, 11, 41, 32, 31, 43, 52, 16, 915, 26, 22, 18, 72, 17, 19,
42, 9, 15, 19, 17, 1, 28, 27, 22, 35, 10, 15, 39, 25, 29, 30, 83,
13, 22, 22, 19, 91, 82, 17, 31, 19, 51, 18, 494, 4, 37, 25, 54, 10,
17, 249, 46, 41, 27, 94, 41, 18, 21, 27, 9, 27, 30, 16, 113, 18, 13,
64, 54, 30),

crciobs=c(62, 391, 97, 96, 87, 39, 152, 98, 96, 117, 92, 51, 111, 138, 35,
11, 66, 130, 538, 42, 103, 73, 75, 102, 104, 41, 2373, 70, 59, 48,
178, 42, 36, 99, 23, 45, 36, 41, 10, 68, 41, 85, 91, 22, 48, 94, 72,
69, 100, 235, 35, 57, 67, 35, 281, 231, 50, 79, 35, 122, 49, 1138,
15, 75, 61, 112, 26, 45, 695, 112, 108, 61, 262, 84, 43, 58, 64, 22,
66, 67, 57, 287, 56, 35, 153, 157, 62),

crcstagn =c(42, 285, 72, 57, 51, 26, 96, 61, 70, 73, 68, 33, 61, 117, 22, 10,
42, 86, 369, 24, 68, 46, 47, 65, 69, 22, 1488, 42, 43, 34, 107, 22,
20, 72, 16, 31, 19, 26, 11, 46, 29, 44, 57, 18, 35, 65, 50, 46, 73,
149, 19, 33, 46, 21, 164, 162, 38, 49, 15, 74, 41, 749, 12, 52, 38,
78, 18, 33, 461, 77, 71, 38, 168, 59, 27, 39, 43, 15, 36, 45, 32,
168, 41, 24, 94, 108, 45),

crcscreen=c(30, 181, 41, 26, 29, 13, 56, 24, 23, 30, 25, 18, 23, 53, 8, 6, 13, 68, 186,
9, 36, 18, 33, 50, 45, 6, 991, 23, 18, 25, 64, 9, 22, 47, 12, 10, 15, 8,
1, 31, 7, 25, 36, 6, 12, 33, 38, 20, 43, 44, 3, 19, 26, 12, 107, 55, 14,
23, 12, 40, 10, 494, 5, 26, 17, 41, 20, 20, 242, 48, 32, 12, 85, 37, 12, 10,
19, 3, 14, 32, 11, 129, 8, 3, 58, 43, 2),

lcdrate = c(
49.85,44.14,47.11,44.32,50.17,40.31,30.91,34.14,44.80,34.04,43.78,32.46,
53.33,31.02,41.65,21.03,32.92,35.27,41.12,31.03,36.73,25.94,33.88,37.35,
32.75,24.84,42.72,41.60,55.75,40.30,51.48,31.05,42.89,30.87,56.37,46.77,
37.73,55.03,48.86,29.51,42.86,36.00,20.80,38.83,23.11,27.25,28.52,46.42,
35.63,39.14,24.78,33.60,31.41,44.54,32.21,33.81,26.57,57.54,35.70,48.40,
45.97,44.66,29.54,32.92,29.70,40.29,36.97,40.63,44.61,38.63,45.26,33.28,
35.78,31.40,29.77,43.56,46.02,35.71,38.93,32.99,34.58,42.12,52.43,26.91,
39.32,38.81,42.83),

lcirate = c(
56.26,49.55,59.01,59.63,55.93,50.03,36.56,40.89,52.12,38.58,62.24,42.43,
60.89,39.31,46.62,47.26,44.08,51.96,49.04,41.72,49.89,40.16,36.93,44.90,
44.26,27.19,53.00,47.60,72.99,49.41,54.94,28.88,47.65,44.59,45.33,54.88,
41.32,58.40,40.33,38.48,36.70,47.81,32.58,66.64,40.12,40.41,25.66,75.87,
50.97,49.62,27.26,45.57,30.55,54.98,51.96,40.70,42.72,66.64,46.22,52.20,
43.76,51.11,36.28,39.49,35.95,49.48,37.15,37.85,53.49,37.87,47.23,40.88,
44.33,42.45,47.52,48.64,40.69,46.55,44.70,53.01,45.80,46.75,53.45,48.02,
47.49,49.29,41.53),

lccursmkpct = c(
29.41,26.05,19.55,21.43,24.11,20.59,20.58,19.17,21.85,22.31,22.05,12.50,
26.95,16.67,23.68,22.86,16.92,23.62,22.02,23.94,13.46,23.16,13.39,22.38,
20.45,27.59,20.75,8.65,23.38,31.30,23.66,23.21,26.32,17.56,12.90,23.88,
33.33,25.45,21.05,20.00,21.05,14.71,21.76,9.09,25.00,12.31,21.95,24.72,
14.62,17.35,18.52,18.69,13.54,25.53,18.54,18.84,14.67,22.11,19.67,20.50,
19.05,22.60,21.43,20.00,20.24,27.24,19.67,24.42,25.40,23.84,27.27,16.90,
20.59,16.56,19.61,22.22,26.88,18.18,25.00,17.02,25.27,21.81,18.60,9.38,
19.74,23.50,17.95),

lcdobs=c(60,447,93,86,80,21,94,69,88,77,86,38,97,95,30,
6,32,132,457,29,84,45,58,93,88,16,2366,57,73,57,
153,29,36,77,25,52,29,49,17,48,33,56,47,16,20,
57,44,64,74,123,22,43,49,30,181,144,25,88,30,114,
41,1223,10,43,51,106,35,37,625,93,84,34,225,58,19,
38,74,16,57,34,42,264,42,15,114,134,43),

lciobs=c(68,519,110,112,82,23,103,77,98,85,118,40,108,111,26,
14,38,181,549,38,101,59,58,104,113,14,2830,61,90,64,
160,28,39,104,19,60,32,50,11,58,26,70,68,23,32,
72,38,98,99,146,22,57,45,32,285,166,41,96,35,116,
38,1331,11,50,51,126,31,30,714,91,86,39,266,78,29,
40,64,21,60,49,52,292,44,21,124,162,40),

lcscreen=c(102,1236,179,182,141,34,311,120,119,260,127,56,141,246,38,
35,65,254,1635,71,156,95,112,143,176,29,6230,104,77,131,
224,56,57,205,31,67,57,55,19,120,19,102,170,22,64,
130,123,89,171,196,27,107,96,47,604,292,75,95,61,161,
42,2739,28,90,84,246,61,86,1051,323,242,71,573,151,51,
27,93,22,56,94,91,949,43,32,304,349,39),

adj = c(11,	31,	69,	9,	58,	33,	48,	18,
27,	71,	30,	13,	82,	62,		
14,	54,	44,	15,	29,	80,	56,	
45,	68,	39,	36,	31,	11,	29,	15,	57,
73,	49,	48,	71,				
78,	75,	76,	37,				
22,	46,	83,	8,	52,	40,	81,		
83,	17,	64,	65,	52,	7,			
1,	69,	58,						
27,	70,	72,	43,	86,				
29,	4,	31,	1,	18,	49,	77,	80,	
37,	76,	34,	65,	87,				
82,	2,	30,	58,					
54,	3,	56,	84,					
60,	57,	4,	29,	3,	44,			
38,								
32,	51,	64,	8,	83,				
11,	1,	48,	49,					
25,	66,	70,	27,	62,	82,			
50,	74,	25,	55,					
61,	26,	56,	77,					
46,	7,	81,	24,					
50,	55,	85,	28,					
22,	81,	74,	50,					
79,	55,	20,	66,	19,				
78,	84,	56,	21,	75,				
19,	70,	10,	86,	2,	62,			
23,	85,							
15,	4,	11,	80,	3,				
2,	71,	48,	33,	13,				
4,	36,	69,	1,	11,				
53,	17,	46,						
48,	1,	58,	30,					
12,	76,	61,	73,	47,	65,			
68,	45,							
39,	4,	31,	69,					
6,	12,	87,						
69,	16,							
68,     4,      36,						
81,	7,	52,	72,	70,	66,			
87,	42,	59,						
41,	87,	64,	51,					
10,	72,	65,	47,	86,				
54,	60,	15,	3,					
35,	68,	4,	57,	60,				
32,	83,	7,	22,					
34,	73,	86,	43,	65,				
5,	49,	18,	1,	33,	30,	71,		
77,	11,	18,	48,	5,	73,			
24,	20,	55,	23,					
53,	59,	42,	64,	17,				
7,	8,	65,	72,	40,				
67,	51,	32,						
60,	44,	3,	14,					
79,	85,	23,	50,	20,	25,			
84,	14,	3,	80,	77,	21,	26,		
45,	4,	15,	63,	60,				
13,	33,	1,	9,					
41,	51,	67,						
45,	57,	63,	15,	44,	54,			
76,	75,	21,	73,	34,				
27,	2,	82,	19,					
60,	57,							
17,	51,	42,	87,	65,	8,			
43,	72,	52,	8,	64,	87,	12,	34,	47,
74,	81,	40,	70,	19,	25,			
59,	53,							
35,	39,	45,	4,					
36,	31,	1,	9,	38,				
66,	40,	72,	10,	27,	19,			
86,	73,	5,	48,	30,	2,			
65,	43,	10,	70,	40,	52,			
86,	47,	34,	61,	77,	49,	5,	71,
24,	81,	66,	20,					
6,	78,	26,	61,	76,				
12,	6,	75,	61,	34,				
21,	56,	80,	11,	49,	73,			
84,	26,	75,	6,					
85,	55,	25,						
56,	3,	29,	11,	77,				
24,	22,	7,	40,	66,	74,			
19,	62,	2,	13,					
46,	17,	8,	7,					
14,	56,	26,	78,					
28,	23,	55,	79,					
47,	73,	71,	27,	10,	43,			
37,	12,	65,	64,	42,	41	),

weights = c(1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1 ),

num = c(8,6,7,9,4,4,7,6,3,5,8,5,4,4,6,1,5,4,6,4,4,4,4,4,5,5,
6,2,5,5,5,3,4,6,2,4,3,2,3,6,3,4,5,4,5,4,5,7,6,4,5,
5,3,4,6,7,5,4,3,6,5,4,2,6,9,6,2,4,5,6,6,6,8,4,5,5,6,
4,3,5,6,4,4,4,4,6,6)

)
		
=========================================================================

bcincidencerate=c(
0.1282,0.0937,0.1083,0.0888,0.0885,0.1292,0.1053,0.0962,0.1041,0.092,0.1293,0.0973,
0.103,0.0987,0.1141,0.0912,0.1114,0.1123,0.1192,0.0962,0.096,0.0747,0.0859,0.0933,
0.1102,0.1444,0.1229,0.1043,0.1111,0.1079,0.1153,0.0771,0.0813,0.1251,0.0816,0.1143,
0.0827,0.1303,0.1186,0.1214,0.0734,0.0946,0.1206,0.0985,0.1079,0.104,0.0901,0.0868,
0.0957,0.0991,0.0846,0.0927,0.0958,0.0725,0.1297,0.1078,0.1315,0.1037,0.1287,0.1077,
0.0902,0.1161,0.0654,0.1034,0.089,0.1114,0.1164,0.1108,0.1059,0.0977,0.1276,0.1234,
0.1101,0.1203,0.0858,0.1252,0.0782,0.1053,0.1066,0.148,0.1105,0.1219,0.095,0.1036,
0.1104,0.0929,0.0854),


bcincidencerate=c(
128200,93700,108300,88800,88500,129200,105300,96200,104100,92000,129300,97300,
103000,98700,114100,91200,111400,112300,119200,96200,96000,74700,85900,93300,
110200,144400,122900,104300,111100,107900,115300,77100,81300,125100,81600,114300,
82700,130300,118600,121400,73400,94600,120600,98500,107900,104000,90100,86800,
95700,99100,84600,92700,95800,72500,129700,107800,131500,103700,128700,107700,
90200,116100,65400,103400,89000,111400,116400,110800,105900,97700,127600,123400,
110100,120300,85800,125200,78200,105300,106600,148000,110500,121900,95000,103600,
110400,92900,85400),


bcmortalityrate=c(
0.0183,0.0217,0.0211,0.0185,0.0187,0.0294,0.0235,0.0175,0.0110,0.0147,
0.0224,0.0216,0.0207,0.0209,0.0398,0.0146,0.0261,0.0286,0.0237,0.0251,
0.0209,0.0261,0.0237,0.0251,0.0352,0.0363,0.0259,0.0263,0.0218,0.0286,
0.0268,0.0313,0.0107,0.0283,0.0318,0.0215,0.0143,0.0227,0.0205,0.0316,
0.0527,0.0271,0.0214,0.0328,0.0120,0.0271,0.0325,0.0266,0.0220,0.0220,
0.0127,0.0171,0.0166,0.0200,0.0251,0.0214,0.0233,0.0194,0.0375,0.0177,
0.0166,0.0229,0.0081,0.0222,0.0203,0.0262,0.0292,0.0245,0.0216,0.0275,
0.0251,0.0428,0.0213,0.0233,0.0265,0.0241,0.0169,0.0372,0.0191,0.0310,
0.0218,0.0226,0.0276,0.0206,0.0155,0.0221,0.0203),