Implemented efficient algorithms for roll_median
and roll_quantile
functions
Fixed an issue for weights
argument if single value (#45)
New roll_crossprod
function for computing rolling and expanding crossproducts of time-series data
Restructured the C++ header files to be used by other packages
Added hex sticker and improved documentation (#27, #28, #30)
New roll_quantile
function for computing rolling and expanding quantiles of time-series data
roll_quantile
function is not calculated using an online algorithmFixed an issue in the roll_min
and roll_max
functions (#32)
Added vector support to each function (#20)
Implemented efficient algorithms for roll_min
and roll_max
functions
New roll_idxmin
and roll_idxmax
functions for computing rolling and expanding indices of minimums and maximums, respectively, of time-series data (#22)
New roll_median
, roll_min
, roll_max
, roll_any
, and roll_all
functions for computing rolling and expanding medians, minimums, maximums, any, and all, respectively, of time-series data (#4, #13, #14)
roll_median
, roll_min
, and roll_max
functions are not calculated using online algorithmsAdded online
argument to process observations using online algorithms by default
roll_lm
function now returns standard errors (#7)
Simplified checks for width
and min_obs
arguments (#3)
Added y
argument to roll_cov
and roll_cor
functions (#2)
Deprecated less common functions (roll_eigen
, roll_vif
, and roll_pcr
) and arguments (scale
and center
in the roll_lm
function); also removed the parallel_for
argument in favor of a new approach used internally
roll_sum
and roll_prod
functions for computing rolling and expanding sums and products, respectively, of time-series dataintercept
argument to roll_lm
and roll_pcr
functionssrc/Makevars
and src/Makevars.win
files (#1)roll_lm
and roll_pcr
functions have been enhanced:
y
can now be a matrix or xts object with multiple dependent variables
Added shorthand arguments for center
and scale
New roll_scale
function for computing rolling and expanding scaling and centering of time-series data