print.mlePT: Methods for objects of class 'mlePT'

In tweeDEseq: RNA-seq data analysis using the Poisson-Tweedie family of distributions

Description

print, extract loglikelihood or compute confidence interval for an object of class 'mlePT'.

Usage

## S3 method for class 'mlePT'
print(x, digits = 3, ...)
## S3 method for class 'mlePT'
logLik(object, ...)
## S3 method for class 'mlePT'
confint(object, parm, level = 0.95, ...)

Arguments

x	object of class 'mlePT'.
object	object of class 'mlePT'.
digits	integer scalar giving the number of digits to be rounded the solution.
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level	the confidence level required (default is 0.95).
...	additional arguments.

Value

'logLik' returns the loglikelihood of the selected model.

'confint' returns a matrix (or vector) with columns giving lower and upper confidence limits for each parameter.

See Also

mlePoissonTweedie

Examples

# Load and aggregate the 'seizure' database
data(seizure)
aggCounts <- aggregate(x = cbind(seizure$count, seizure$trx), by =
list(seizure$id), FUN = sum)

# Estimate the parameters
mleSeizure <- mlePoissonTweedie(x = aggCounts[,2], a.ini = 0, D.ini =
10)

# Print
mleSeizure

# Extract loglikelihood
logLik(mleSeizure)

# Compute confidence inerval
confint(mleSeizure)

tweeDEseq documentation built on Nov. 8, 2020, 5:59 p.m.