tidychangepoint (version 1.0.0)

as.ts.mod_cpt: Objects exported from other packages

Description

These objects are imported from other packages. Follow the links below to see their documentation.

broom

augment, glance, tidy

stats

AIC, as.ts, BIC, coef, fitted, logLik, nobs, residuals, time

vctrs

vec_cast, vec_ptype2

zoo

index

Usage

# S3 method for mod_cpt
as.ts(x, ...)
# S3 method for mod_cpt
nobs(object, ...)
# S3 method for mod_cpt
logLik(object, ...)
# S3 method for mod_cpt
fitted(object, ...)
# S3 method for mod_cpt
residuals(object, ...)
# S3 method for mod_cpt
coef(object, ...)
# S3 method for mod_cpt
augment(x, ...)
# S3 method for mod_cpt
tidy(x, ...)
# S3 method for mod_cpt
glance(x, ...)
# S3 method for mod_cpt
plot(x, ...)
# S3 method for mod_cpt
print(x, ...)
# S3 method for seg_basket
as.ts(x, ...)
# S3 method for seg_basket
plot(x, ...)
# S3 method for seg_cpt
as.ts(x, ...)
# S3 method for seg_cpt
glance(x, ...)
# S3 method for seg_cpt
nobs(object, ...)
# S3 method for seg_cpt
print(x, ...)
# S3 method for tidycpt
as.ts(x, ...)
# S3 method for tidycpt
augment(x, ...)
# S3 method for tidycpt
tidy(x, ...)
# S3 method for tidycpt
glance(x, ...)
# S3 method for tidycpt
plot(x, use_time_index = FALSE, ...)
# S3 method for tidycpt
print(x, ...)
# S3 method for meanshift_lnorm
logLik(object, ...)
# S3 method for nhpp
logLik(object, ...)
# S3 method for nhpp
glance(x, ...)
# S3 method for ga
as.ts(x, ...)
# S3 method for ga
nobs(object, ...)
# S3 method for cpt
as.ts(x, ...)
# S3 method for cpt
logLik(object, ...)
# S3 method for cpt
nobs(object, ...)
# S3 method for wbs
as.ts(x, ...)
# S3 method for wbs
nobs(object, ...)

Arguments

...

some methods for this generic function require additional arguments.

object

any object from which a log-likelihood value, or a contribution to a log-likelihood value, can be extracted.

use_time_index

Should the x-axis labels be the time indices? Or the time labels?

Examples

# Plot a meanshift model fit
plot(fit_meanshift_norm(CET, tau = 330))

#' # Plot a trendshift model fit
plot(fit_trendshift(CET, tau = 330))

#' # Plot a quadratic polynomial model fit
plot(fit_lmshift(CET, tau = 330, deg_poly = 2))

#' # Plot a 4th degree polynomial model fit
plot(fit_lmshift(CET, tau = 330, deg_poly = 10))

# Plot a segmented time series
plot(segment(CET, method = "pelt"))

# Plot a segmented time series and show the time labels on the x-axis
plot(segment(CET, method = "pelt"), use_time_index = TRUE)