# === Targets -------------------------------------------------------------
# Alec L. Robitaille
# Source ------------------------------------------------------------------
lapply(dir('R', '*.R', full.names = TRUE), source)
# Options -----------------------------------------------------------------
# Targets
tar_option_set(format = 'qs')
# Stan
options(mc.cores = 2,
scipen = 999,
digits = 2)
# Targets: homework 2 -----------------------------------------------------
targets_h02 <- c(
tar_target(
Howell_lt_12,
data_Howell()[age < 12]
),
tar_target(
m_h02_q02,
brm(
weight ~ age,
prior = c(
prior(normal(4, 0.5), Intercept),
prior(normal(4, 1), b),
prior(exponential(1), sigma)
),
data = Howell_lt_12
)
),
tar_target(
m_h02_q03,
brm(
weight ~ age + sex,
prior = c(
prior(normal(4, 0.5), Intercept),
prior(normal(4, 1), b),
prior(exponential(1), sigma)
),
data = Howell_lt_12
)
)
)
# Targets: homework 3 -----------------------------------------------------
targets_h03 <- c(
tar_target(
foxes,
data_foxes(scale = TRUE)
),
tar_target(
m_h03_q01_prior,
brm(
scale_avgfood ~ scale_area,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h03_q01,
brm(
scale_avgfood ~ scale_area,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes
)
),
tar_target(
m_h03_q02_prior,
brm(
scale_weight ~ scale_avgfood,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h03_q02,
brm(
scale_weight ~ scale_avgfood,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes
)
),
tar_target(
m_h03_q03_prior,
brm(
scale_weight ~ scale_avgfood + scale_groupsize,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h03_q03,
brm(
scale_weight ~ scale_avgfood + scale_groupsize,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes
)
),
tar_target(
m_h03_q03_groupsize_food,
brm(
scale_groupsize ~ scale_avgfood,
prior = c(
prior(normal(0, 0.25), Intercept),
prior(normal(0, 0.5), b),
prior(exponential(1), sigma)
),
data = foxes
)
)
)
# Targets: homework 5 -----------------------------------------------------
targets_h05 <- c(
tar_target(
DT_grants,
data_grants()
),
tar_target(
m_h05_q01_prior,
brm(
awards | trials(applications) ~ gender,
family = 'binomial',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1), class = Intercept)
),
data = DT_grants,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h05_q01,
brm(
awards | trials(applications) ~ gender,
family = 'binomial',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1), class = Intercept)
),
data = DT_grants
)
),
tar_target(
m_h05_q02,
brm(
awards | trials(applications) ~ gender * discipline,
family = 'binomial',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1), class = Intercept)
),
data = DT_grants
)
)
)
# Targets: homework 6 -----------------------------------------------------
targets_h06 <- c(
tar_target(
DT_frogs,
data_reedfrogs()
),
tar_target(
m_h06_q01_prior_exp_1,
brm(
surv | trials(density) ~ (1 | tank),
family = 'binomial',
prior = c(
prior(normal(0, 1), class = Intercept),
prior(exponential(1), class = sd)
),
data = DT_frogs,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h06_q01_prior_exp_0pt1,
brm(
surv | trials(density) ~ (1 | tank),
family = 'binomial',
prior = c(
prior(normal(0, 1), class = Intercept),
prior(exponential(0.1), class = sd)
),
data = DT_frogs,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h06_q01_prior_exp_10,
brm(
surv | trials(density) ~ (1 | tank),
family = 'binomial',
prior = c(
prior(normal(0, 1), class = Intercept),
prior(exponential(10), class = sd)
),
data = DT_frogs,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h06_q02,
brm(
surv | trials(density) ~ pred * size + (1 | tank),
family = 'binomial',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1), class = Intercept),
prior(exponential(1), class = sd)
),
data = DT_frogs
)
),
tar_target(
m_h06_q03,
brm(
surv | trials(density) ~ pred * density + (1 | tank),
family = 'binomial',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1), class = Intercept),
prior(exponential(1), class = sd)
),
data = DT_frogs
)
)
)
# Targets: homework 9 -----------------------------------------------------
targets_h09 <- c(
tar_target(
DT_hunting,
data_achehunting()
),
tar_target(
m_h09_q01_prior,
brm(
success ~ s(age),
family = 'bernoulli',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1.5), class = Intercept),
prior(exponential(1), class = sds)
),
data = DT_hunting,
sample_prior = 'only',
chains = 1
)
),
tar_target(
m_h09_q01,
brm(
success ~ s(age),
family = 'bernoulli',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1.5), class = Intercept),
prior(exponential(1), class = sds)
),
data = DT_hunting
)
),
tar_target(
m_h09_q02,
brm(
success ~ t2(age, by = id),
family = 'bernoulli',
prior = c(
prior(normal(0, 0.5), class = b),
prior(normal(0, 1.5), class = Intercept),
prior(exponential(1), class = sds)
),
data = DT_hunting
)
),
# tar_target(
# m_h09_q02_s_var_id,
# brm(
# success ~ s(age) + (1 | id),
# family = 'bernoulli',
# prior = c(
# prior(normal(0, 0.5), class = b),
# prior(normal(0, 1.5), class = Intercept),
# prior(exponential(1), class = sds),
# prior(exponential(1), class = sd)
# ),
# data = DT_hunting
# )
# ),
# tar_target(
# m_h09_q03_complete_cases,
# brm(
# success ~ t2(age, hours, by = id),
# family = 'bernoulli',
# prior = c(
# prior(normal(0, 0.5), class = b),
# prior(normal(0, 1.5), class = Intercept),
# prior(exponential(1), class = sds)
# ),
# data = na.omit(DT_hunting)
# )
# ),
tar_target(
DT_hunting_mice,
mice(DT_hunting)
)#,
# tar_target(
# m_h09_q03_mice,
# brm_multiple(
# success ~ t2(age, hours, by = id),
# family = 'bernoulli',
# prior = c(
# prior(normal(0, 0.5), class = b),
# prior(normal(0, 1.5), class = Intercept),
# prior(exponential(1), class = sds)
# ),
# data = DT_hunting_mice
# )
# )
)
# Lecture 19 --------------------------------------------------------------
targets_lecture_19 <- c(
tar_target(
m_l19_nl_howell,
brm(
bf(
scale_weight_div_mean ~ log(k * 3.1415 * p ^ 2 * scale_height_div_mean ^ 3),
p ~ 1,
k ~ 1,
nl = TRUE),
prior = c(
prior(beta(25, 50), nlpar = p, lb = 0, ub = 1),
prior(exponential(0.5), nlpar = k, lb = 0),
prior(exponential(1), class = sigma)
),
data = data_Howell(),
family = 'lognormal'
)
),
tar_target(
m_l19_nl_howell_no_dim,
brm(
bf(
scale_weight_div_mean ~ log(scale_height_div_mean ^ 3)),
prior = c(
prior(exponential(1), class = sigma)
),
data = data_Howell(),
family = 'lognormal'
)
)
)
# Quarto ------------------------------------------------------------------
targets_quarto <- c(
tar_quarto(site, path = '.')#, cue = tar_cue('never'))
)
# Targets: all ------------------------------------------------------------
# Automatically grab all the "targets_*" lists above
lapply(grep('targets', ls(), value = TRUE), get)