Thanks to Jim Maas, shreydesai, Breza, CameronNemo for reporting bugs Thanks to for Sebastian Gatscha providing the (way faster) C++ na.ma() implementation
tibble and tstibble compatibility
Reworked internal code documentation
na.ma speed up via C++
Changed vignette builder to R.rsp
Used R package styler package to optimize source code readability
Made some changes to better follow tidyverse style guide
Replaced na. with na_ e.g na.mean with na_mean usw.This fits better to modern code style guidelines. The old function names will still work for a while, but give a warning.
Added findFrequency option to na.seadec and na.seasplit
Added maxgap option
Fixed bug for na.seadec - also imputed known values in some special cases (reported by CameronNemo)
Added doi: 10.32614/RJ-2017-009 to describtion, references, readme and citation file
Added StackExchange link to Readme
Moved stinepack from imports to suggested
Internal reorganization of imports - now always using pkg::function and importFrom pkg x1 x2 x3instead of just import pkg
Fixed bug in na.ma when using xts time series with NA at the end
Fixed error message in na.interpolation if wrong parameter is given
stop(“Wrong parameter ‘option’ given. Value must be either ‘linear’, ‘spline’ or ‘stine’.”) (reported by Breza)
Fixed spelling mistakes in na.seadec and na.seasplit (reported by shreydesai)
Fixed bug with na.random() output (reported by Jim Maas)
Better plots using ggplot2
Better and more unit tests
Additional vignettes
Adding harmonic and geometric mean as option for na_mean
Updated Description: Orcid Id added, packages required for unit test add as “Suggested”
Small correction in README.md, small update to citation file
Replaced NEWS with NEWS.md for better formatting
Updated citation file
Minor changes to vignette
Small speed improvments for na.kalman
Improved input check for all functions
Bugfix for unit tests
Changes to unit test (because of zoo update)
Bugfix for na.kalman with integer input
Readme Update
Improved error messages for na.seasplit and na.seadec
Minor vignette changes
Fixed for problems with Solaris/Sparc
Fixes for problems with vignette on osx
Bugfix for plots without missing data
Increased performance for na.locf
Minor bugfixes for specific data.frame inputs
Minor bugfixes for specific xts object inputs
Improved Code Documentation
Added new software tests
Computation time improvments for na.locf (up to 10000 times faster)
Computation time improvments for na.interpolation (up to 10000 times faster)
Computation time improvments for na.kalman (only slightly faster, under 10%)
Fixed unnecessary warning message with some na.kalman options
Adjusted default parameters for plotNA.distributionBar (using nclass.Sturges for breaks parameter)
Fixed issue with too sensitive input checking
Enabled usage of multivariate input (data.frame, mts, matrix,…) for all imputation functions except na.remove. This means users do not have to loop through all columns by themselfes anymore if they want to use the package with multivariate data. The imputation itself is still performend in univariate manner (column after column).
Improved compatibility with different advanced time series objects like zoo and xts. Using the imputation functions with these time series objects should be possible now. These series will not be explicitly named as possible input in the user documentation. Absence of errors can not be guaranteed. However, there are no known issues yet.
Added several things for unit tests with pkg ‘testthat’
Added unit tests for every function
Adjusted error messages
Internal Coding style improvement: replaced all T with TRUE and all F with FALSE
Adjustment tsHeating / tsHeatingComplete datasets (set 1440 as frequency parameter)
Adjustment tsNH4 / tsNH4Complete datasets (set 144 as frequency parameter)
Fixes for grammar, spelling and citations in the whole documentation
Revised examples in the documentation for all functions
Restricted output of na.remove to vector only (issue with incorrect time information otherwise)
Added better x-axes labels for plotNA.distribution
Added github links to description file
Added citation file
Updated Readme (badges for travis ci and cran status)
Fix in documentation for na.interpolation (due to outdated descriptions)
Fix in documentation plotNA.distribution / plotNA.distributionBar (due to interchanged descriptions)
Added references to used packages in na.kalman and na.interpolation documentation
Allows now also numeric vectors as input
Removed na.identifier parameter for all functions (too error prone, better handled individually by the user)
Minor changes in na.interpolation with option = “stine”
Added na.ma imputation function
Replaced “data” in all function parameters with the more common “x”
Improvement of all code examples
Renamed heating/heatingComplete dataset to tsHeating/tsHeatingComplete
Renamed nh4/nh4Complete dataset to tsNH4/tsNH4Complete
Added tsAirgap / tsAirgapComplete datasets
Improved imputeTS-package documentation
Added na.kalman imputation function
Added README.md function
Added statsNA function
Added plotNA.gapsize function
Renamed vis.imputations to plotNA.imputations
Renamed vis.barMissing to plotNA.distributionBar
Renamed vis.missing to plotNA.distribution
Fixed issues with parameter pass through and legend for all plotting functions
Improved dataset documentation
Update of vis.differences (better looking plot now)
Added vis.missing to visualize the distribution of missing data in a time series
Added vis.barMissing, which is especially suited to visualize missing data in very huge time series
Update na.interpolate (added Stineman interpolation and enabled … parameter for all interpolation algorithms to pass through parameters to the underlying functions)
Added two datasets of sensor data
vis.differences for plotting differences between real and imputed values
Removed internal functions from visible package documentation
Added additional algorithms: na.seasplit and na.seadec
internal function for algorithm selection
Created initial version of imputeTS package for univariate time series imputation
added the simple imputation functions: na.locf, na.mean, na.random, na.interpolation, na.replace
added na.remove function for removing all NAs from a time series