fastcpd to the top in the README.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.load
fastcpd 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.