likelihood {bayesplay} | R Documentation |
Define likelihoods using different different distribution families #nolint
likelihood(family, ...)
family |
the likelihood distribution (see details) |
... |
see details |
The following distribution families can be used for the likelihood
normal
a normal distribution
student_t
a scaled and shifted t-distribution
noncentral_t
a noncentral t (for t statistic)
noncentral_d
a noncentral t (for one sample d)
noncentral_d2
a noncentral t (for independent samples d)
binomial
a binomial distribution
The parameters that need to be specified will be dependent on the
family
When family
is set to normal
then the following
parameters must be set
mean
mean of the normal likelihood
sd
standard deviation of the normal likelihood
When family
is set to student_t
then the following
parameters may be set
mean
mean of the scaled and shifted t likelihood
sd
standard deviation of the scaled and shifted t likelihood
df
degrees of freedom
When family
is set to noncentral_t
then the following
parameters may be set
t
the t value of the data
df
degrees of freedom
When family
is set to noncentral_d
then the following
parameters may be set
d
the d (mean / sd) value of the data
n
the sample size
When family
is set to noncentral_d2
then the following
parameters may be set
d
the d (mean / s_pooled) value of the data
n1
the sample size of group 1
n2
the sample size of group 2
s_pooled is set as below:
√(((n1 - 1) * s1^2 + (n2 - 1)*s2^2)/(n1 + n2 - 2))
When the family
is set to binomial
then the following
parameters may be set
successes
the number of successes
trials
the number of trials
an object of class likelihood
# specify a normal likelihood likelihood(family = "normal", mean = 5.5, sd = 32.35) # specify a scaled and shifted t likelihood likelihood(family = "student_t", mean = 5.5, sd = 32.35, df = 10) # specify non-central t likelihood (t scaled) likelihood(family = "noncentral_t", t = 10, df = 10) # specify non-central t likelihood (d scaled) likelihood(family = "noncentral_d", d = 10, n = 10) # specify non-central t likelihood (independent samples d scaled) likelihood(family = "noncentral_d2", d = 10, n1 = 10, n2 = 12) # specify a binomial likelihood likelihood(family = "binomial", successes = 2, trials = 10)