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
.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.
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
.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.