StatsBernoulli {bfw} | R Documentation |
Bernoulli Trials
Description
Conduct bernoulli trials
Usage
StatsBernoulli(
x = NULL,
x.names = NULL,
DF,
params = NULL,
initial.list = list(),
...
)
Arguments
x |
predictor variable(s), Default: NULL |
x.names |
optional names for predictor variable(s), Default: NULL |
DF |
data for analysis |
params |
define parameters to observe, Default: NULL |
initial.list |
initial values for analysis, Default: list() |
... |
further arguments passed to or from other methods |
See Also
Examples
## Create coin toss data: heads = 50 and tails = 50
#fair.coin<- as.matrix(c(rep("Heads",50),rep("Tails",50)))
#colnames(fair.coin) <- "X"
#fair.coin <- bfw(project.data = fair.coin,
# x = "X",
# saved.steps = 50000,
# jags.model = "bernoulli",
# jags.seed = 100,
# ROPE = c(0.4,0.6),
# silent = TRUE)
#fair.coin.freq <- binom.test( 50000 * 0.5, 50000)
## Create coin toss data: heads = 20 and tails = 80
#biased.coin <- as.matrix(c(rep("Heads",20),rep("Tails",80)))
#colnames(biased.coin) <- "X"
#biased.coin <- bfw(project.data = biased.coin,
# x = "X",
# saved.steps = 50000,
# jags.model = "bernoulli",
# jags.seed = 101,
# initial.list = list(theta = 0.7),
# ROPE = c(0.4,0.6),
# silent = TRUE)
#biased.coin.freq <- binom.test( 50000 * 0.8, 50000)
## Print Bayesian and frequentist results of fair coin
#fair.coin$summary.MCMC[,c(3:6,9:12)]
## Mode ESS HDIlo HDIhi ROPElo ROPEhi ROPEin n
## 0.505 50480.000 0.405 0.597 2.070 2.044 95.886 100.00
#sprintf("Frequentist: %.3f [%.3f , %.3f], p = %.3f" ,
# fair.coin.freq$estimate ,
# fair.coin.freq$conf.int[1] ,
# fair.coin.freq$conf.int[2] ,
# fair.coin.freq$p.value)
## [1] "Frequentist: 0.500 [0.496 , 0.504], p = 1.000"
## Print Bayesian and frequentist results of biased coin
#biased.coin$summary.MCMC[,c(3:6,9:12)]
## Mode ESS HDIlo HDIhi ROPElo ROPEhi ROPEin n
## 0.803 50000.000 0.715 0.870 0.000 99.996 0.004 100.000
#sprintf("Frequentist: %.3f [%.3f , %.3f], p = %.3f" ,
# biased.coin.freq$estimate ,
# biased.coin.freq$conf.int[1] ,
# biased.coin.freq$conf.int[2] ,
# biased.coin.freq$p.value)
## [1] "Frequentist: 0.800 [0.796 , 0.803], p = 0.000"
[Package bfw version 0.4.2 Index]