summary.singleRStaticCountData | R Documentation |
A summary
method for singleRStaticCountData
class
## S3 method for class 'singleRStaticCountData'
summary(
object,
test = c("t", "z"),
resType = "pearson",
correlation = FALSE,
confint = FALSE,
cov,
popSizeEst,
...
)
object |
object of singleRStaticCountData class. |
test |
type of test for significance of parameters |
resType |
type of residuals to summarize any value that is allowed in
|
correlation |
logical value indicating whether correlation matrix should
be computed from covariance matrix by default |
confint |
logical value indicating whether confidence intervals for
regression parameters should be constructed. By default |
cov |
covariance matrix corresponding to regression parameters.
It is possible to give |
popSizeEst |
a |
... |
additional optional arguments passed to the following functions:
|
Works
analogically to summary.glm
but includes population size estimation
results. If any additional statistics, such as confidence intervals for
coefficients or coefficient correlation, are specified they will be printed.
An object of summarysingleRStaticCountData
class containing:
call
– A call which created object
.
coefficients
– A dataframe with estimated regression coefficients
and their summary statistics such as standard error Wald test statistic and
p value for Wald test.
residuals
– A vector of residuals of type specified at call.
aic
– Akaike's information criterion.
bic
– Bayesian (Schwarz's) information criterion.
iter
– Number of iterations taken in fitting regression.
logL
– Logarithm of likelihood function evaluated at coefficients.
deviance
– Residual deviance.
populationSize
– Object with population size estimation results.
dfResidual
– Residual degrees of freedom.
sizeObserved
– Size of observed population.
correlation
– Correlation matrix if correlation
parameter was set to TRUE
test
– Type of statistical test performed.
model
– Family class object specified in call for object
.
skew
– If bootstrap sample was saved contains estimate of skewness.
redoPopEstimation()
stats::summary.glm()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.