print.cauphyfit {cauphy} | R Documentation |
Generic Methods for S3 class cauphyfit
.
Description
Generic Methods for S3 class cauphyfit
.
Usage
## S3 method for class 'cauphyfit'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'cauphyfit'
vcov(object, ...)
## S3 method for class 'cauphyfit'
logLik(object, ...)
## S3 method for class 'logLik.cauphyfit'
AIC(object, k = 2, ...)
## S3 method for class 'cauphyfit'
AIC(object, k = 2, ...)
## S3 method for class 'cauphyfit'
confint(object, parm, level = 0.95, ...)
## S3 method for class 'cauphyfit'
coef(object, ...)
Arguments
x |
an object of class |
digits |
number of digits to show in summary method. |
... |
further arguments to methods. |
object |
an object of class |
k |
numeric, the penalty per parameter to be used; the default |
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. |
Value
Same value as the associated methods from the stats
package:
vcov
an estimated covariance matrix, see
compute_vcov
;logLik
an object of class
logLik
;AIC
a numeric value;
confint
a matrix (or vector) with columns giving lower and upper confidence limits for each parameter;
coef
coefficients extracted from the model;
See Also
fitCauchy
, vcov
, logLik
AIC
, confint
, coef
,
predict
, predict.phylolm
Examples
# Simulate tree and data
set.seed(1289)
phy <- ape::rphylo(20, 0.1, 0)
dat <- rTraitCauchy(n = 1, phy = phy, model = "cauchy",
parameters = list(root.value = 10, disp = 0.1))
# Fit the data
fit <- fitCauchy(phy, dat, model = "cauchy", method = "reml")
fit
# vcov matrix
vcov(fit)
# Approximate confidence intervals
confint(fit)
# log likelihood of the fitted object
logLik(fit)
# AIC of the fitted object
AIC(fit)
# coefficients
coef(fit)