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Fixes for JAGS 5.0.0. Reduce variance of diffuse normal priors. #4

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Fixes for JAGS 5.0.0. Reduce variance of diffuse normal priors. #4

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6 changes: 3 additions & 3 deletions R/hurdle.R
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Original file line number Diff line number Diff line change
Expand Up @@ -600,8 +600,8 @@ hurdle <- function(data, model.eff, model.cost, model.se = se ~ 1, model.sc = sc
if(exists("gamma.prior.c", where = prior)) {gamma.prior.c = prior$gamma.prior.c} else {gamma.prior.c = NULL }
if(exists("gamma0.prior.e", where = prior)) {gamma0.prior.e = prior$gamma0.prior.e} else {gamma0.prior.e = NULL }
if(exists("gamma0.prior.c", where = prior)) {gamma0.prior.c = prior$gamma0.prior.c} else {gamma0.prior.c = NULL }
if(exists("se.prior", where = prior)) {se.prior = prior$se.prior} else {se.prior = 0.0000001 }
if(exists("sc.prior", where = prior)) {sc.prior = prior$sc.prior} else {sc.prior = 0.0000001 }
if(exists("se.prior", where = prior)) {se.prior = prior$se.prior} else {se.prior = 0.001 }
if(exists("sc.prior", where = prior)) {sc.prior = prior$sc.prior} else {sc.prior = 0.001 }
if(exists("beta_f.prior", where = prior)) {beta_f.prior = prior$beta_f.prior} else {beta_f.prior = NULL }
if(exists("mu.a0.prior", where = prior)) {mu.a0.prior = prior$mu.a0.prior} else {mu.a0.prior = NULL }
if(exists("s.a0.prior", where = prior)) {s.a0.prior = prior$s.a0.prior} else {s.a0.prior = NULL }
Expand Down Expand Up @@ -684,4 +684,4 @@ hurdle <- function(data, model.eff, model.cost, model.se = se ~ 1, model.sc = sc
res <- list(data_set = data_set, model_output = model_output, cea = cea, type = type, data_format = format)
class(res) <- "missingHE"
return(res)
}
}
38 changes: 19 additions & 19 deletions R/prior_hurdle.R
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Original file line number Diff line number Diff line change
Expand Up @@ -139,24 +139,24 @@ prior_hurdle <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed, zc
if(length(alpha0.prior) != 2) {stop("provide correct hyper prior values") }
prior_mue <- alpha0.prior
prior_mue_str <- paste("alpha1[1] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha1[1] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("alpha1[1] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags, fixed = TRUE)
prior_mue_str <- paste("alpha2[1] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha2[1] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("alpha2[1] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags, fixed = TRUE) }
} else if(pe_fixed > 1){
if(is.null(alpha0.prior) == FALSE & grepl("alpha1[1, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("alpha2[1, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(alpha0.prior) != 2) {stop("provide correct hyper prior values") }
prior_mue <- alpha0.prior
prior_mue_str <- paste("alpha1[1, 1] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha1[1, 1] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("alpha1[1, 1] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags, fixed = TRUE)
prior_mue_str <- paste("alpha2[1, 1] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha2[1, 1] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("alpha2[1, 1] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags, fixed = TRUE) }
if(is.null(alpha.prior) == FALSE & grepl("alpha1[j, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("alpha2[j, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(alpha.prior) != 2) {stop("provide correct hyper prior values") }
prior_alphae <- alpha.prior
prior_alphae_str <- paste("alpha1[j, 1] ~ dnorm(", prior_alphae[1], ",", prior_alphae[2])
model_string_jags <- gsub("alpha1[j, 1] ~ dnorm(0, 0.0000001", prior_alphae_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("alpha1[j, 1] ~ dnorm(0, 0.001", prior_alphae_str, model_string_jags, fixed = TRUE)
prior_alphae_str <- paste("alpha2[j, 1] ~ dnorm(", prior_alphae[1],",", prior_alphae[2])
model_string_jags <- gsub("alpha2[j, 1] ~ dnorm(0, 0.0000001", prior_alphae_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("alpha2[j, 1] ~ dnorm(0, 0.001", prior_alphae_str, model_string_jags, fixed = TRUE) }
}
if(length(model_e_random) != 0 & pe_random == 1) {
if(is.null(mu.a0.prior) == FALSE & grepl("mu_a_hat[t] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
Expand Down Expand Up @@ -186,31 +186,31 @@ prior_hurdle <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed, zc
if(length(beta0.prior) != 2) {stop("provide correct hyper prior values") }
prior_muc <- beta0.prior
prior_muc_str <- paste("beta1[1] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta1[1] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta1[1] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE)
prior_muc_str <- paste("beta2[1] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta2[1] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta2[1] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE) }
} else if(pc_fixed > 1) {
if(is.null(beta.prior) == FALSE & grepl("beta1[1] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("beta2[1] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(beta.prior) != 2) {stop("provide correct hyper prior values") }
prior_muc <- beta.prior
prior_muc_str <- paste("beta1[1] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta1[1] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta1[1] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE)
prior_muc_str <- paste("beta2[1] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta2[1] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta2[1] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE) }
if(is.null(beta0.prior) == FALSE & grepl("beta1[1, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("beta2[1, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(beta0.prior) != 2) {stop("provide correct hyper prior values") }
prior_muc <- beta0.prior
prior_muc_str <- paste("beta1[1, 1] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta1[1, 1] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta1[1, 1] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE)
prior_muc_str <- paste("beta2[1, 1] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta2[1, 1] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta2[1, 1] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE) }
if(is.null(beta.prior) == FALSE & grepl("beta1[j, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("beta2[j, 1] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(beta.prior) != 2){stop("provide correct hyper prior values") }
prior_betac <- beta.prior
prior_betac_str <- paste("beta1[j, 1] ~ dnorm(", prior_betac[1], ",", prior_betac[2])
model_string_jags <- gsub("beta1[j, 1] ~ dnorm(0, 0.0000001", prior_betac_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta1[j, 1] ~ dnorm(0, 0.001", prior_betac_str, model_string_jags, fixed = TRUE)
prior_betac_str <- paste("beta2[j, 1] ~ dnorm(", prior_betac[1], ",", prior_betac[2])
model_string_jags <- gsub("beta2[j, 1] ~ dnorm(0, 0.0000001", prior_betac_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta2[j, 1] ~ dnorm(0, 0.001", prior_betac_str, model_string_jags, fixed = TRUE) }
}
if(length(model_c_random) != 0 & pc_random == 1) {
if(is.null(mu.b0.prior) == FALSE & grepl("mu_b_hat[t] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
Expand Down Expand Up @@ -390,15 +390,15 @@ prior_hurdle <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed, zc
if(is.null(se) == FALSE & is.null(sc) == TRUE) {
prior_beta_f <- beta_f.prior
prior_beta_f_str <- paste("beta_f[1] ~ dnorm(", prior_beta_f[1], ",", prior_beta_f[2])
model_string_jags <- gsub("beta_f[1] ~ dnorm(0, 0.0000001", prior_beta_f_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta_f[1] ~ dnorm(0, 0.001", prior_beta_f_str, model_string_jags, fixed = TRUE)
prior_beta_f_str <- paste("beta_f[2] ~ dnorm(", prior_beta_f[1], ",", prior_beta_f[2])
model_string_jags <- gsub("beta_f[2] ~ dnorm(0, 0.0000001", prior_beta_f_str, model_string_jags, fixed = TRUE)}
model_string_jags <- gsub("beta_f[2] ~ dnorm(0, 0.001", prior_beta_f_str, model_string_jags, fixed = TRUE)}
if(is.null(sc) == FALSE) {
prior_beta_f <- beta_f.prior
prior_beta_f_str <- paste("beta_f1[1] ~ dnorm(", prior_beta_f[1], ",", prior_beta_f[2])
model_string_jags <- gsub("beta_f1[1] ~ dnorm(0, 0.0000001", prior_beta_f_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta_f1[1] ~ dnorm(0, 0.001", prior_beta_f_str, model_string_jags, fixed = TRUE)
prior_beta_f_str <- paste("beta_f2[1] ~ dnorm(", prior_beta_f[1], ",",prior_beta_f[2])
model_string_jags <- gsub("beta_f2[1] ~ dnorm(0, 0.0000001", prior_beta_f_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta_f2[1] ~ dnorm(0, 0.001", prior_beta_f_str, model_string_jags, fixed = TRUE) }
}
}
if(exists("mu.b_f.prior") == TRUE) {
Expand All @@ -419,4 +419,4 @@ prior_hurdle <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed, zc
}
model_string_prior <- model_string_jags
return(model_string_prior)
}))
}))
32 changes: 16 additions & 16 deletions R/prior_long_miss.R
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Original file line number Diff line number Diff line change
Expand Up @@ -165,22 +165,22 @@ prior_long_miss <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed,
if(length(alpha0.prior) != 2) {stop("provide correct hyper prior values") }
prior_mue <- alpha0.prior
prior_mue_str <- paste("alpha[1, time] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha[1, time] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags,fixed = TRUE)
model_string_jags <- gsub("alpha[1, time] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags,fixed = TRUE)
prior_mue_str <- paste("alpha[2, time] ~ dnorm(", prior_mue[1],",", prior_mue[2])
model_string_jags <- gsub("alpha[2, time] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("alpha[2, time] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags, fixed = TRUE) }
} else if(pe_fixed > 1){
if(is.null(alpha0.prior) == FALSE & grepl("alpha[1, 1, time] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("alpha[1, 2, time] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(alpha0.prior) != 2) {stop("provide correct hyper prior values") }
prior_mue <- alpha0.prior
prior_mue_str <- paste("alpha[1, 1, time] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha[1, 1, time] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags,fixed = TRUE)
model_string_jags <- gsub("alpha[1, 1, time] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags,fixed = TRUE)
prior_mue_str <- paste("alpha[1, 2, time] ~ dnorm(", prior_mue[1], ",", prior_mue[2])
model_string_jags <- gsub("alpha[1, 2, time] ~ dnorm(0, 0.0000001", prior_mue_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("alpha[1, 2, time] ~ dnorm(0, 0.001", prior_mue_str, model_string_jags, fixed = TRUE) }
if(is.null(alpha.prior) == FALSE & grepl("alpha[j, t, time] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(alpha.prior) != 2) {stop("provide correct hyper prior values") }
prior_alphae <- alpha.prior
prior_alphae_str <- paste("alpha[j, t, time] ~ dnorm(", prior_alphae[1], ",", prior_alphae[2])
model_string_jags <- gsub("alpha[j, t, time] ~ dnorm(0, 0.0000001", prior_alphae_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("alpha[j, t, time] ~ dnorm(0, 0.001", prior_alphae_str, model_string_jags, fixed = TRUE) }
}
if(length(model_e_random) != 0 & pe_random == 1) {
if(is.null(mu.a0.prior) == FALSE & grepl("mu_a_hat[t, time] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
Expand Down Expand Up @@ -210,22 +210,22 @@ prior_long_miss <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed,
if(length(beta0.prior) != 2) {stop("provide correct hyper prior values") }
prior_muc <- beta0.prior
prior_muc_str <- paste("beta[1, time] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta[1, time] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta[1, time] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE)
prior_muc_str <- paste("beta[2, time] ~ dnorm(",prior_muc[1],",", prior_muc[2])
model_string_jags <- gsub("beta[2, time] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta[2, time] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE) }
} else if(pc_fixed > 1) {
if(is.null(beta0.prior) == FALSE & grepl("beta[1, 1, time] ~ ", model_string_jags, fixed = TRUE) == TRUE & grepl("beta[1, 2, time] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(beta0.prior) != 2) {stop("provide correct hyper prior values") }
prior_muc <- beta0.prior
prior_muc_str <- paste("beta[1, 1, time] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta[1, 1, time] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta[1, 1, time] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE)
prior_muc_str <- paste("beta[1, 2, time] ~ dnorm(", prior_muc[1], ",", prior_muc[2])
model_string_jags <- gsub("beta[1, 2, time] ~ dnorm(0, 0.0000001", prior_muc_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta[1, 2, time] ~ dnorm(0, 0.001", prior_muc_str, model_string_jags, fixed = TRUE) }
if(is.null(beta.prior) == FALSE & grepl("beta[j, t, time] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
if(length(beta.prior) != 2){stop("provide correct hyper prior values") }
prior_betac <- beta.prior
prior_betac_str <- paste("beta[j, t, time] ~ dnorm(", prior_betac[1], ",", prior_betac[2])
model_string_jags <- gsub("beta[j, t, time] ~ dnorm(0, 0.0000001", prior_betac_str, model_string_jags, fixed = TRUE) }
model_string_jags <- gsub("beta[j, t, time] ~ dnorm(0, 0.001", prior_betac_str, model_string_jags, fixed = TRUE) }
}
if(length(model_c_random) != 0 & pc_random == 1) {
if(is.null(mu.b0.prior) == FALSE & grepl("mu_b_hat[t, time] ~ ", model_string_jags, fixed = TRUE) == TRUE) {
Expand Down Expand Up @@ -308,7 +308,7 @@ prior_long_miss <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed,
if(length(beta_f.prior) != 2) {stop("provide correct hyper prior values") }
prior_beta_f <- beta_f.prior
prior_beta_f_str <- paste("beta_f[t, time] ~ dnorm(", prior_beta_f[1], ",", prior_beta_f[2])
model_string_jags <- gsub("beta_f[t, time] ~ dnorm(0, 0.0000001", prior_beta_f_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta_f[t, time] ~ dnorm(0, 0.001", prior_beta_f_str, model_string_jags, fixed = TRUE)
}
}
if(exists("mu.b_f.prior") == TRUE) {
Expand All @@ -332,15 +332,15 @@ prior_long_miss <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed,
if(length(beta_te.prior) != 2) {stop("provide correct hyper prior values") }
prior_beta_te <- beta_te.prior
prior_beta_te_str <- paste("beta_te[t, time] ~ dnorm(", prior_beta_te[1], ",", prior_beta_te[2])
model_string_jags <- gsub("beta_te[t, time] ~ dnorm(0, 0.0000001", prior_beta_te_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta_te[t, time] ~ dnorm(0, 0.001", prior_beta_te_str, model_string_jags, fixed = TRUE)
}
}
if(exists("beta_tc.prior") == TRUE) {
if(is.null(beta_tc.prior) == FALSE & grepl("beta_tc", model_string_jags, fixed = TRUE) == TRUE) {
if(length(beta_tc.prior) != 2) {stop("provide correct hyper prior values") }
prior_beta_tc <- beta_tc.prior
prior_beta_tc_str <- paste("beta_tc[t, time] ~ dnorm(", prior_beta_tc[1], ",", prior_beta_tc[2])
model_string_jags <- gsub("beta_tc[t, time] ~ dnorm(0, 0.0000001", prior_beta_tc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("beta_tc[t, time] ~ dnorm(0, 0.001", prior_beta_tc_str, model_string_jags, fixed = TRUE)
}
}
if(exists("mu.b_te.prior") == TRUE) {
Expand Down Expand Up @@ -380,15 +380,15 @@ prior_long_miss <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed,
if(length(alpha_te.prior) != 2) {stop("provide correct hyper prior values") }
prior_alpha_te <- alpha_te.prior
prior_alpha_te_str <- paste("alpha_te[t, time] ~ dnorm(", prior_alpha_te[1], ",", prior_alpha_te[2])
model_string_jags <- gsub("alpha_te[t, time] ~ dnorm(0, 0.0000001", prior_alpha_te_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("alpha_te[t, time] ~ dnorm(0, 0.001", prior_alpha_te_str, model_string_jags, fixed = TRUE)
}
}
if(exists("alpha_tc.prior") == TRUE) {
if(is.null(alpha_tc.prior) == FALSE & grepl("alpha_tc", model_string_jags, fixed = TRUE) == TRUE) {
if(length(alpha_tc.prior) != 2) {stop("provide correct hyper prior values") }
prior_alpha_tc <- alpha_tc.prior
prior_alpha_tc_str <- paste("alpha_tc[t, time] ~ dnorm(", prior_alpha_tc[1], ",", prior_alpha_tc[2])
model_string_jags <- gsub("alpha_tc[t, time] ~ dnorm(0, 0.0000001", prior_alpha_tc_str, model_string_jags, fixed = TRUE)
model_string_jags <- gsub("alpha_tc[t, time] ~ dnorm(0, 0.001", prior_alpha_tc_str, model_string_jags, fixed = TRUE)
}
}
if(exists("mu.a_te.prior") == TRUE) {
Expand Down Expand Up @@ -425,4 +425,4 @@ prior_long_miss <- function(type, dist_e, dist_c, pe_fixed, pc_fixed , ze_fixed,
}
model_string_prior <- model_string_jags
return(model_string_prior)
}))
}))
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