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Merged
jtimonen merged 6 commits into from
Dec 5, 2025
Merged

v0.3.3 #50

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1f78526
Increment version number to 0.3.1.9000
jtimonen Dec 5, 2025
c777d9e
fix ss xpsr
jtimonen Dec 5, 2025
4e40698
set default norm
jtimonen Dec 5, 2025
124c529
Increment version number to 0.3.2
jtimonen Dec 5, 2025
2a0727b
safety edit
jtimonen Dec 5, 2025
67c8755
Increment version number to 0.3.3
jtimonen Dec 5, 2025
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
Package: bmstate
Type: Package
Title: Bayesian multistate modeling
Version: 0.3.1
Version: 0.3.3
Authors@R:
c(person(given = "Juho",
family = "Timonen",
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2 changes: 1 addition & 1 deletion R/MultistateModel.R
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Expand Up @@ -47,7 +47,7 @@ MultistateModel <- R6::R6Class("MultistateModel",
categorical = NULL,
normalizer_locations = NULL,
normalizer_scales = NULL,
xpsr_normalizer_loc = 7.5,
xpsr_normalizer_loc = 5.5, # corresponds to about dose=30
xpsr_normalizer_scale = 0.5,
n_grid = NULL,
simulate_log_hazard_multipliers = function(df_subjects, beta) {
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2 changes: 1 addition & 1 deletion R/MultistateModelFit.R
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Expand Up @@ -414,7 +414,7 @@ msmfit_exposure <- function(fit, oos = FALSE, data = NULL) {
out <- list()
for (s in seq_len(S)) {
if (sd$do_pk == 1) {
x_xpsr <- log_ss_area_under_conc(sd$dose_ss, log_pkpar[[s]]) # log D/(CL*V2)
x_xpsr <- log_ss_area_under_conc(sd$dose_ss, log_pkpar[[s]]) # log D/CL
} else {
x_xpsr <- NULL
}
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4 changes: 1 addition & 3 deletions R/PKModel.R
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Expand Up @@ -110,11 +110,9 @@ PKModel <- R6::R6Class("PKModel",
#' @return A numeric value
compute_xpsr = function(theta, dose) {
CL <- theta[2]
V2 <- theta[3]
checkmate::assert_number(CL, lower = 0)
checkmate::assert_number(V2, lower = 0)
checkmate::assert_number(dose, lower = 0)
log(dose) - log(CL) - log(V2)
log(dose) - log(CL)
},

#' @description Simulate data with many subjects
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3 changes: 1 addition & 2 deletions R/stan.R
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Expand Up @@ -102,8 +102,7 @@ fit_stan <- function(model, data,
model$set_normalizers(data)
if (!is.null(data$dosing)) {
log_mu_CL <- -2 # should match msm.stan
log_mu_V2 <- -2 # should match msm.stan
aaa <- log(data$dosing$dose_ss) - log_mu_CL - log_mu_V2
aaa <- log(data$dosing$dose_ss) - log_mu_CL
loc <- mean(aaa)
sca <- stats::sd(aaa)
model$set_xpsr_normalizers(loc, sca)
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4 changes: 2 additions & 2 deletions inst/stan/msm.stan
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Expand Up @@ -2,7 +2,7 @@ functions {

// log SS AUC
vector log_ss_area_under_conc(vector dose_ss, matrix log_theta_pk){
return(log(dose_ss) - log_theta_pk[:,2] - log_theta_pk[:,3]) ; // log D/(CL*V2)
return(log(dose_ss) - log_theta_pk[:,2]) ; // log D/CL
}

// log of hazard multiplier
Expand Down Expand Up @@ -448,7 +448,7 @@ model {
if(do_haz == 1){
if(nc_haz > 0){
for(k in 1:nc_haz){
beta_oth[1, k] ~ normal(0, 2);
beta_oth[1, k] ~ normal(0, 1);
}
}
if(I_xpsr==1){
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2 changes: 1 addition & 1 deletion vignettes/analysis.Rmd
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Expand Up @@ -142,7 +142,7 @@ mod$get_knots()
We fit the model by optimizing.

```{r}
fit <- fit_stan(mod, data = pd, method = "optimize")
fit <- fit_stan(mod, data = pd, method = "optimize", init = 0.1)
```

## Inferred baseline hazards
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