## ----echo = FALSE-------------------------------------------------------------
rm(list = ls())
library(EMC2)
## ----results = "hide"---------------------------------------------------------
rm(list = ls())
library(EMC2)
## ----echo=TRUE, message=FALSE, warning=FALSE, results='hide'------------------
matchfun <- function(d) d$S == d$lR
design_LBA <- design(factors=list(subjects=1,S=c("left", "right")),
Rlevels = c("left", "right"),
matchfun = matchfun,
formula =list(v~lM,B~1, t0~1, sv~1, A~1),
constants=c(sv=log(1)),
model = LBA)
prior_LBA <- prior(design_LBA, type = "single",
pmean = c(1.3, .7, log(.8), log(.2), log(.3)),
psd = c(.2, .1, .1, .05, .05))
## ----fig.alt = "Prior for LBA non-hierarchical model", fig.height = 5---------
plot(prior_LBA)
## ----eval=FALSE---------------------------------------------------------------
# SBC_LBA_single <- run_sbc(design_LBA, prior_LBA, replicates = 500, trials = 100, plot_data = FALSE,
# iter = 1000, n_post = 1000, fileName = "SBC_data/SBC_LBA_single.RData",
# cores_per_chain = 30)
## ----include=FALSE------------------------------------------------------------
load("SBC_data/SBC_LBA_single.RData")
## ----fig.height = 6, fig.alt = "Histogram SBC LBA single"---------------------
plot_sbc_hist(SBC_LBA_single, bins = 10)
## ----fig.height = 6, fig.alt = "ecdf LBA single"------------------------------
plot_sbc_ecdf(SBC_LBA_single)
## ----echo=TRUE, message=FALSE, warning=FALSE, results='hide', eval = FALSE----
# #?DDM
# design_DDM <- design(factors=list(subjects=1,S=c("left", "right")),
# Rlevels = c("left", "right"),
# formula =list(v~1,a~1, t0~1, s~1, Z~1, sv~1, SZ~1, st0 ~ 1),
# constants=c(s=log(1)),
# model = DDM)
#
#
# prior_DDM <- prior(design_DDM, type = "single",
# pmean = c(1, log(.8), log(.3), qnorm(.5), log(.1), qnorm(.05), log(.05)),
# psd = c(.15, .15, .1, .05, .15, .15, .15))
#
# SBC_DDM_single <- run_sbc(design_DDM, prior_DDM, replicates = 500, trials = 100,
# fileName = "SBC_data/SBC_DDM_single.RData", cores_per_chain = 30)
#
## ----include=FALSE------------------------------------------------------------
load("SBC_data/SBC_DDM_single.RData")
## ----fig.height = 6, fig.alt = "ecdf DDM single", fig.width= 10---------------
plot_sbc_ecdf(SBC_DDM_single)
## ----echo=TRUE, message=FALSE, warning=FALSE, results='hide'------------------
n_subjects <- 30
#
matchfun <- function(d) d$S == d$lR
design_LBA <- design(factors=list(subjects=1:n_subjects,S=c("left", "right")),
Rlevels = c("left", "right"),
matchfun = matchfun,
formula =list(v~lM,B~1, t0~1, sv~1, A~1),
constants=c(sv=log(1)),
model = LBA)
prior_LBA <- prior(design_LBA, type = "diagonal-gamma",
mu_mean = c(1.3, .7, log(.8), log(.2), log(.3)),
mu_sd = c(.2, .1, .1, .05, .05),
shape = 10,
rate = c(.2, .2, .2, .1, .1))
## ----fig.alt = "Prior for LBA hierarchical model", fig.height = 5-------------
plot(prior_LBA, selection = "alpha")
## ----eval=FALSE---------------------------------------------------------------
# SBC_LBA <- run_sbc(design_LBA, prior_LBA, replicates = 500, trials = 100,
# n_subjects = n_subjects, fileName = "SBC_data/SBC_LBA.RData", cores_per_chain = 30)
## ----include=FALSE------------------------------------------------------------
load("SBC_data/SBC_LBA.RData")
## ----fig.height = 6, fig.alt = "ECDF SBC LBA"---------------------------------
plot_sbc_ecdf(SBC_LBA)
## ----echo=TRUE, message=FALSE, warning=FALSE, results='hide'------------------
n_subjects <- 30
design_DDM <- design(factors=list(subjects=1:n_subjects,S=c("left", "right")),
Rlevels = c("left", "right"),
formula =list(v~1,a~1, t0~1, s~1, Z~1, sv~1, SZ~1, st0 ~ 1),
constants=c(s=log(1)),
model = DDM)
prior_DDM <- prior(design_DDM, type = "diagonal-gamma",
pmean = c(1.2, log(.8), log(.3), qnorm(.5), log(.1), qnorm(.05), log(.05)),
psd = c(.15, .15, .1, .05, .1, .1, .15),
shape = 10,
rate = c(.2, .2, .2, .1, .1, .1, .1))
## ----eval=FALSE---------------------------------------------------------------
# SBC_DDM <- run_sbc(design_DDM, prior_DDM, replicates = 250, trials = 200,
# n_subjects = n_subjects, fileName = "SBC_data/SBC_DDM.RData", cores_per_chain = 30)
## ----include=FALSE------------------------------------------------------------
load("SBC_data/SBC_DDM.RData")
## ----fig.height = 7, fig.alt = "ECDF SBC DDM"---------------------------------
plot_sbc_ecdf(SBC_DDM)
## ----echo=TRUE, eval = FALSE--------------------------------------------------
# n_subjects <- 30
#
# matchfun <- function(d) d$S == d$lR
#
#
# design_RDM <- design(factors=list(subjects=1:n_subjects,S=c("left", "right")),
# Rlevels = c("left", "right"),
# matchfun = matchfun,
# formula =list(v~lM,B~1, t0~1, A~1, s ~ 1),
# constants=c(s=log(1)),
# model = RDM)
#
# prior_RDM <- prior(design_RDM, type = "diagonal-gamma",
# mu_mean = c(1.4, .3, log(1.5), log(.2), log(.3)),
# mu_sd = c(.05, .1, .1, .05, .05),
# shape = 10,
# rate = c(.1, .2, .2, .2, .1))
#
# SBC_RDM <- run_sbc(design_RDM, prior_RDM, replicates = 500, trials = 100,
# n_subjects = n_subjects, fileName = "SBC_RDM.RData", cores_per_chain = 30)
#
## ----include=FALSE------------------------------------------------------------
load("SBC_data/SBC_RDM.RData")
## ----fig.height = 6, fig.alt = "ECDF SBC RDM"---------------------------------
plot_sbc_ecdf(SBC_RDM)
## ----echo=TRUE, eval = FALSE--------------------------------------------------
# n_subjects <- 30
#
# matchfun <- function(d) d$S == d$lR
#
# design_LNR <- design(factors=list(subjects=1:n_subjects,S=c("left", "right")),
# Rlevels = c("left", "right"),
# matchfun = matchfun,
# formula =list(m~lM,s~1, t0~1),
# model = LNR)
#
# prior_LNR <- prior(design_LNR, type = "diagonal-gamma",
# mu_mean = c(-.7, -.5, log(1), log(.2)),
# mu_sd = c(.2, .1, .1, .05),
# shape = 10,
# rate = c(.2, .2, .2, .1))
#
# SBC_LNR <- run_sbc(design_LNR, prior_LNR, replicates = 500, trials = 100,
# n_subjects = n_subjects, fileName = "SBC_LNR.RData", cores_per_chain = 30)
#
## ----include=FALSE------------------------------------------------------------
load("SBC_data/SBC_LNR.RData")
## ----fig.height = 6, fig.alt = "ECDF SBC RDM"---------------------------------
plot_sbc_ecdf(SBC_LNR, layout = c(2,2))