An S4 class to hold the output of a call to zlm

Description

This holds output from a call to zlm. Many methods are defined to operate on it. See below.

Usage

## S4 method for signature 'ZlmFit,CoefficientHypothesis'
lrTest(object, hypothesis)

## S4 method for signature 'ZlmFit,Hypothesis'
lrTest(object, hypothesis)

## S4 method for signature 'ZlmFit,matrix'
lrTest(object, hypothesis)

## S4 method for signature 'ZlmFit,CoefficientHypothesis'
waldTest(object, hypothesis)

## S4 method for signature 'ZlmFit,Hypothesis'
waldTest(object, hypothesis)

## S4 method for signature 'ZlmFit'
coef(object, which, ...)

## S4 method for signature 'ZlmFit'
vcov(object, which, ...)

## S4 method for signature 'ZlmFit'
se.coef(object, which, ...)

Arguments

Value

see "Methods (by generic)"

Methods (by generic)

• lrTest: Returns an array with likelihood-ratio tests on contrasts defined using CoefficientHypothesis().

• lrTest: Returns an array with likelihood-ratio tests specified by Hypothesis, which is a Hypothesis.

• lrTest: Returns an array with likelihood-ratio tests specified by Hypothesis, which is a contrast matrix.

• waldTest: Returns an array with Wald Tests on contrasts defined using CoefficientHypothesis().

• waldTest: Returns an array with Wald Tests on contrasts defined in Hypothesis()

• coef: Returns the matrix of coefficients for component which.

• vcov: Returns an array of variance/covariance matrices for component which.

• se.coef: Returns a matrix of standard error estimates for coefficients on component which.

Slots

coefC

matrix of continuous coefficients

coefD

matrix of discrete coefficients

vcovC

array of variance/covariance matrices for coefficients

vcovD

array of variance/covariance matrices for coefficients

LMlike

the LmWrapper object used

sca

the SingleCellAssay object used

deviance

matrix of deviances

loglik

matrix of loglikelihoods

df.null

matrix of null (intercept only) degrees of freedom

df.resid

matrix of residual DOF

dispersion

matrix of dispersions (after shrinkage)

dispersionNoShrink

matrix of dispersion (before shrinkage)

priorDOF

shrinkage weight in terms of number of psuedo-obs

priorVar

shrinkage target

converged

output that may optionally be set by the underlying modeling function

hookOut

a list of length ngenes containing output from a hook function, if zlm was called with one

See Also

zlm summary,ZlmFit-method

Examples

data(vbetaFA)
zlmVbeta <- zlm(~ Stim.Condition+Population, subset(vbetaFA, ncells==1)[1:10,])
#Coefficients and standard errors
coef(zlmVbeta, 'D')
coef(zlmVbeta, 'C')
se.coef(zlmVbeta, 'C')
#Test for a Population effect by dropping the whole term (a 5 degree of freedom test)
lrTest(zlmVbeta, 'Population')
#Test only if the VbetaResponsive cells differ from the baseline group
lrTest(zlmVbeta, CoefficientHypothesis('PopulationVbetaResponsive'))
# Test if there is a difference between CD154+/Unresponsive and CD154-/Unresponsive.
# Note that because we parse the expression
# the columns must be enclosed in backquotes
# to protect the \quote{+} and \quote{-} characters.
lrTest(zlmVbeta, Hypothesis('`PopulationCD154+VbetaUnresponsive` -
        `PopulationCD154-VbetaUnresponsive`'))
waldTest(zlmVbeta, Hypothesis('`PopulationCD154+VbetaUnresponsive` -
        `PopulationCD154-VbetaUnresponsive`'))