trim value.variance_estimation allowing users to
specify the variance or covariance matrix if known.fastcpd_impl API for use in other packages.eval = FALSE.lasso.gfpop due to
https://github.com/doccstat/fastcpd/issues/10.pruning parameter and replace with
convexity_coef = -Inf.well_log.well_log data.winsorize_minval and
winsorize_maxval.CptNonPar,
gfpop, InspectChangepoint,
jointseg, Rbeast and
VARDetect.Note: From now on, MBIC is used as the default
penalty selection for beta parameter.
Add penalty selection criteria using
(p + 1) * log(nrow(data)) / 2(p + 2) * log(nrow(data)) / 2 with
adjusted cost function.(p + 2) * log(nrow(data)) / 2 with adjusted cost
function.In the mean time, a numeric value can be passed to beta
as well to explicitly specify the penalty for BIC.
Remove bcp according to
Package ‘bcp’ was removed from the CRAN repository.
Formerly available versions can be obtained from the archive.
Archived on 2024-01-12 as email to the maintainer is undeliverable.
A summary of the most recent check results can be obtained from the check results archive.
Please use the canonical form https://CRAN.R-project.org/package=bcp to link to this page.interactive() to check if the current R session is
interactive.order = c(p, q) and family "arma".fastcpd.arma / fastcpd_arma for
ARMA(p, q) model.beta values.lower and upper parameters to denote
the lower and upper bounds of the parameters.bitcoin and well_log data.fastcpd.ar /
fastcpd_ar, ARIMA(p, d, q) family:
fastcpd.arima / fastcpd_arima, GARCH(p, q)
family: fastcpd.garch / fastcpd_garch, linear
regression family: fastcpd.lm / fastcpd_lm,
logistic regression family: fastcpd.binomial /
fastcpd_binomial, poisson regression family:
fastcpd.poisson / fastcpd_poisson, penalized
linear regression family: fastcpd.lasso /
fastcpd_lasso, MA(q) model: fastcpd.ma /
fastcpd_ma, mean change: fastcpd.mean /
fastcpd_mean, variance change:
fastcpd.variance / fastcpd_variance, mean or
variance change: fastcpd.meanvariance /
fastcpd_meanvariance / fastcpd.mv /
fastcpd_mv."gaussian" family with "lm".vanilla_percentage
parameter.beta is updated but the old
beta is still in use.beta updating into
get_segment_statistics.forecast package for ARIMA model.fGarch package for GARCH model.&& around || by
parentheses.cost_function_wrapper.fastcpd.ts / fastcpd_ts for time
series data.lasso.vanilla_percentage parameter for
lasso.fastcpd.ts.cp_only = TRUE default when the family is
“custom”.cp_only = TRUE and
fastcpd_ts.ggplot2 is not
installed.Deal with the following:
Due to the excessive calls to `glmnet` between R and C++,
it is better to use the R implementation of `fastcpd` for lasso.Separate the use of internal C++ cost functions and user-defined R cost functions.
Add Codecov Icicle plot in README.
Remove cost_optim and cost_update from
RcppExports.R.
Estimate the variance in the “gaussian” family dynamically.
fastcpd definition.length(formals(cost)) to check the number
of arguments of cost function.family.ggplot2 is not installed.forecast example in the tests.fastcpd documentation.formula.Add suggested package checking in tests.
Try to solve the amazing clang-ASAN error on CRAN:
Error in dyn.load(file, DLLpath = DLLpath, ...) :
unable to load shared object '/data/gannet/ripley/R/test-clang/mvtnorm/libs/mvtnorm.so':
/data/gannet/ripley/R/test-clang/mvtnorm/libs/mvtnorm.so: undefined symbol: _ZNK7Fortran7runtime10Terminator5CrashEPKcz
Calls: <Anonymous> ... asNamespace -> loadNamespace -> library.dynam -> dyn.loadfastcpd method.R CMD Rd2pdf . --output=man/figures/manual.pdf --force --no-preview
from stackoverflow.glmnet.vanilla_percentage parameter.fastcpd parameters updating in C++.theta_hat,
theta_sum and hessian.vanilla_percentage to denote the method
switching between vanilla PETL and SeN.cp_only parameter.fastcpd.fastcpd.lfactorial.pkgdown
generated webpage.fastcpd.fastcpd class.thetas slot in fastcpd
class.cp_only to FALSE.summary method.fastcpd
function.NEWS.md file to track changes to the
package.