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Test STAN m4.6
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@lacorreia65
lacorreia65 committed Jan 30, 2023
1 parent 9514f00 commit 3c93721
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136 changes: 68 additions & 68 deletions .Rhistory
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Original file line number Diff line number Diff line change
@@ -1,37 +1,3 @@
}"
data_m4.5 <- list(
N = nrow(d),
height = d$height,
weight_s = d$weight_s,
weight_s2 = d$weight_s2
)
#fit_m4.5 <- stan(data = data_m4.5, model_code = stan_m4.5,
# chains = 3, iter = 1000)
fit_m4.6 <- stan(data = data_m4.5, model_code = stan_m4.6,
chains = 3, iter = 1000)
traceplot(fit_m4.5, pars = "b1")
traceplot(fit_m4.6, pars = "beta1")
traceplot(fit_m4.6, pars = "sigma")
print(fit_m4.6)
# Same Model in STAN
stan_m4.6 <- "
data {
int<lower = 1> N;
vector[N] height;
vector[N] weight_s;
vector[N] weight_s2;
}
transformed data{
real bar_x1;
real x1_sd;
vector[N] x1_std;
real y_sd;
bar_x1 = mean(weight_s);
x1_sd = sd(weight_s);
x1_std = (weight_s - bar_x1)/x1_sd; // centered and scaled
y_sd = sd(height);
}
parameters {
real alpha_std;
real beta1_std;
real beta3_std;
Expand All @@ -48,8 +14,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ uniform(0,50);
// sigma ~ exponential(1/y_sd);
// sigma ~ uniform(0,50);
sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
}
Expand All @@ -70,7 +36,25 @@ weight_s2 = d$weight_s2
)
fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
traceplot(fit_m4.6, pars = "sigma")
summary(fit_m4.6)
print(fit_m4.6, pars = c("alpha"))
print(fit_m4.6, pars = c("alpha"))
print(fit_m4.6, pars = c("alpha","beta1", "beta3"))
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
precis(m4.5)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std"))
precis(m4.5)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std", "sigma"))
precis(m4.5)
sigma_sample <- extract(fit_mn)[["sigma"]]
sigma_sample <- extract(fit_m4.6)[["sigma"]]
hist(sigma_sample)
# Same Model in STAN
stan_m4.6 <- "
data {
Expand Down Expand Up @@ -106,8 +90,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ uniform(0,8);
// sigma ~ exponential(1/y_sd);
sigma ~ uniform(5,3);
// sigma ~ exponential(1/y_sd); // WHY?????
// model
height ~normal(mu,sigma);
}
Expand All @@ -128,6 +112,7 @@ weight_s2 = d$weight_s2
)
fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
# Same Model in STAN
stan_m4.6 <- "
Expand Down Expand Up @@ -164,8 +149,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
// sigma ~ uniform(0,50);
sigma ~ exponential(1/y_sd);
sigma ~ uniform(5,3);
// sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
}
Expand All @@ -186,8 +171,8 @@ weight_s2 = d$weight_s2
)
fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
traceplot(fit_m4.6, pars = "sigma")
# Same Model in STAN
stan_m4.6 <- "
data {
Expand Down Expand Up @@ -223,8 +208,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
// sigma ~ uniform(0,50);
sigma ~ exponential(1/y_sd);
sigma ~ normal(5,3);
// sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
}
Expand All @@ -247,23 +232,10 @@ fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
traceplot(fit_m4.6, pars = "sigma")
summary(fit_m4.6)
print(fit_m4.6, pars = c("alpha"))
print(fit_m4.6, pars = c("alpha"))
print(fit_m4.6, pars = c("alpha","beta1", "beta3"))
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
precis(m4.5)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std"))
precis(m4.5)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std", "sigma"))
precis(m4.5)
sigma_sample <- extract(fit_mn)[["sigma"]]
sigma_sample <- extract(fit_m4.6)[["sigma"]]
hist(sigma_sample)
traceplot(fit_m4.6, pars = "sigma")
# Same Model in STAN
stan_m4.6 <- "
data {
Expand Down Expand Up @@ -299,8 +271,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ uniform(5,3);
// sigma ~ exponential(1/y_sd); // WHY?????
sigma ~ normal(5,1.5);
// sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
}
Expand All @@ -323,6 +295,32 @@ fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std", "sigma"))
precis(m4.5)
traceplot(fit_m4.6, pars = "sigma")
sigma_sample <- extract(fit_m4.6)[["sigma"]]
hist(sigma_sample)
library(rethinking)
library(tidyverse)
library(dplyr)
library(ggplot2)
library(rstan)
data(Howell1)
# d <-Howell1[Howell1$age>=18,]
d <-Howell1
d$weight_s <-(d$weight-mean(d$weight))/sd(d$weight)
d$weight_s2 <-d$weight_s^2
m4.5 <-quap(
alist(
height ~dnorm(mu,sigma),
mu <-a+b1*weight_s+b2*weight_s2,
a ~dnorm(178,20),
b1 ~dlnorm(0,1),
b2 ~dnorm(0,1),
sigma ~dunif(0,50)
) ,data=d)
precis(m4.5)
# Same Model in STAN
stan_m4.6 <- "
data {
Expand Down Expand Up @@ -358,7 +356,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ uniform(5,3);
sigma ~ uniform(1,7);
// sigma ~ normal(5,1.5);
// sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
Expand All @@ -382,6 +381,10 @@ fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std", "sigma"))
precis(m4.5)
traceplot(fit_m4.6, pars = "sigma")
# Same Model in STAN
stan_m4.6 <- "
data {
Expand Down Expand Up @@ -417,7 +420,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ normal(5,3);
sigma ~ uniform(0,50);
// sigma ~ normal(5,1.5);
// sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
Expand All @@ -441,10 +445,8 @@ fit_m4.6 <- stan(data = data_m4.6,
model_code = stan_m4.6,
chains = 4,
iter = 2000)
print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std", "sigma"))
precis(m4.5)
traceplot(fit_m4.6, pars = "sigma")
sigma_sample <- extract(fit_m4.6)[["sigma"]]
# Same Model in STAN
stan_m4.6 <- "
data {
Expand Down Expand Up @@ -480,8 +482,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ normal(5,1.5);
// sigma ~ exponential(1/y_sd);
//sigma ~ normal(5,1.5);
sigma ~ exponential(1/y_sd);
// model
height ~normal(mu,sigma);
}
Expand All @@ -508,5 +510,3 @@ print(fit_m4.6, pars = c("alpha","beta1", "beta3", "sigma"))
print(fit_m4.6, pars = c("alpha_std","beta1_std", "beta3_std", "sigma"))
precis(m4.5)
traceplot(fit_m4.6, pars = "sigma")
sigma_sample <- extract(fit_m4.6)[["sigma"]]
hist(sigma_sample)
10 changes: 5 additions & 5 deletions .Rproj.user/B584AE7E/sources/per/t/77F68D30
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Expand Up @@ -3,7 +3,7 @@
"path": "C:/Users/lacor/OneDrive/100. Personal/SelfDevelopment/25. Project 2022/Statistical-Thinking-2023/Statistical Thinking 2023_v2.qmd",
"project_path": "Statistical Thinking 2023_v2.qmd",
"type": "quarto_markdown",
"hash": "59382345",
"hash": "2945690342",
"contents": "",
"dirty": false,
"created": 1673908998203.0,
Expand All @@ -15,18 +15,18 @@
"source_window_id": "",
"Source": "Source",
"docOutlineVisible": "1",
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},
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"lastKnownWriteTime": 1674978203,
"lastKnownWriteTime": 1675068098,
"encoding": "UTF-8",
"collab_server": "",
"source_window": "",
"last_content_update": 1674978203724,
"last_content_update": 1675068098355,
"read_only": false,
"read_only_alternatives": []
}
4 changes: 2 additions & 2 deletions .Rproj.user/B584AE7E/sources/per/t/77F68D30-contents
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Expand Up @@ -775,8 +775,8 @@ model {
alpha_std ~ normal(0,20);
beta1_std ~ normal(0,2);
beta3_std ~ normal(0,2);
sigma ~ normal(5,1.5);
// sigma ~ exponential(1/y_sd);
//sigma ~ normal(5,1.5);
sigma ~ exponential(1/y_sd);

// model
height ~normal(mu,sigma);
Expand Down
2 changes: 1 addition & 1 deletion .Rproj.user/B584AE7E/sources/per/t/FA83A758
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Expand Up @@ -13,7 +13,7 @@
"source_window_id": "",
"Source": "Source",
"cursorPosition": "662,35",
"scrollLine": "649"
"scrollLine": "0"
},
"folds": "",
"lastKnownWriteTime": 1667249148,
Expand Down
2 changes: 1 addition & 1 deletion .Rproj.user/B584AE7E/sources/prop/12DA31F2
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Expand Up @@ -2,5 +2,5 @@
"source_window_id": "",
"Source": "Source",
"cursorPosition": "662,35",
"scrollLine": "649"
"scrollLine": "0"
}
4 changes: 2 additions & 2 deletions .Rproj.user/B584AE7E/sources/prop/EA93BB00
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Expand Up @@ -4,8 +4,8 @@
"source_window_id": "",
"Source": "Source",
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"docOutlineSize": "118"
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5 changes: 0 additions & 5 deletions ....user/shared/notebooks/39C21CC9-Statistical Thinking 2023_v2/1/s/c0qzt99s3uz17/00000f.csv
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44 changes: 39 additions & 5 deletions ....user/shared/notebooks/39C21CC9-Statistical Thinking 2023_v2/1/s/c5ns7cfqmp4sr/00000f.csv
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@@ -1,4 +1,23 @@
"0","library(rethinking)"
"2","Loading required package: rstan
"
"2","Loading required package: StanHeaders
"
"2","
rstan version 2.26.13 (Stan version 2.26.1)

"
"2","For execution on a local, multicore CPU with excess RAM we recommend calling
options(mc.cores = parallel::detectCores()).
To avoid recompilation of unchanged Stan programs, we recommend calling
rstan_options(auto_write = TRUE)
For within-chain threading using `reduce_sum()` or `map_rect()` Stan functions,
change `threads_per_chain` option:
rstan_options(threads_per_chain = 1)

"
"2","Do not specify '-march=native' in 'LOCAL_CPPFLAGS' or a Makevars file
"
"2","Loading required package: cmdstanr
"
"2","This is cmdstanr version 0.5.3
Expand All @@ -21,18 +40,33 @@ Attaching package: ‘rethinking’

stan

"
"2","The following object is masked from ‘package:purrr’:

map

"
"2","The following object is masked from ‘package:stats’:

rstudent

"
"0","library(tidyverse)"
"2","Registered S3 methods overwritten by 'dbplyr':
method from
print.tbl_lazy
print.tbl_sql
"
"2","── Attaching packages ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.2 ──"
"2","✔ ggplot2 3.4.0 ✔ purrr  0.3.5
✔ tibble  3.1.8 ✔ dplyr  1.0.10
✔ tidyr  1.2.1 ✔ stringr 1.4.1
✔ readr  2.1.3 ✔ forcats 0.5.2 "
"2","Warning: package ‘ggplot2’ was built under R version 4.2.2"
"2","Warning: package ‘tidyr’ was built under R version 4.2.2"
"2","Warning: package ‘readr’ was built under R version 4.2.2"
"2","Warning: package ‘purrr’ was built under R version 4.2.2"
"2","Warning: package ‘dplyr’ was built under R version 4.2.2"
"2","── Conflicts ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ tidyr::extract() masks rstan::extract()
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
✖ purrr::map() masks rethinking::map()"
"0","library(dplyr)"
"0","library(ggplot2)"
"0","library(rstan)"
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