1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
|
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 6,
fig.height = 6
)
## ----echo = TRUE--------------------------------------------------------------
library("brglm2")
data("alligators", package = "brglm2")
## ----echo = TRUE--------------------------------------------------------------
agresti_contrasts <- list(lake = contr.treatment(levels(alligators$lake), base = 4),
size = contr.treatment(levels(alligators$size), base = 2))
all_ml <- brmultinom(foodchoice ~ size + lake , weights = freq,
data = alligators,
contrasts = agresti_contrasts,
ref = 1,
type = "ML")
all_ml_summary <- summary(all_ml)
## Estimated regression parameters
round(all_ml_summary$coefficients, 2)
## Estimated standard errors
round(all_ml_summary$standard.errors, 2)
## ----echo = TRUE--------------------------------------------------------------
all_mean <- update(all_ml, type = "AS_mean")
summary(all_mean)
## ----echo = TRUE--------------------------------------------------------------
all_median <- update(all_ml, type = "AS_median")
summary(all_median)
## ----echo = TRUE, error = TRUE------------------------------------------------
all_ml_sparse <- update(all_ml, weights = round(freq/3), slowit = 0.1)
summary(all_ml_sparse)
## ----echo = TRUE--------------------------------------------------------------
library("detectseparation")
se_ratios <- check_infinite_estimates(all_ml_sparse)
plot(se_ratios)
## ----echo = TRUE--------------------------------------------------------------
all_mean_sparse <- update(all_ml_sparse, type = "AS_mean")
summary(all_mean_sparse)
all_median_sparse <- update(all_ml_sparse, type = "AS_median")
summary(all_median_sparse)
|
