Imports: foreach, graphics, mcGlobaloptim, methods, lubridate, stats
Packaged: 2021-04-21 15:10:29 UTC; striaukas

Packaged: 2021-04-22 12:09:50 UTC; striaukas

Packaged: 2021-04-23 10:05:18 UTC; striaukas

Packaged: 2021-05-20 08:07:10 UTC; striaukas

Packaged: 2021-05-05 14:23:57 UTC; striaukas

Packaged: 2021-11-30 13:59:50 UTC; Utilisateur

Imports: doRNG, doParallel, foreach, graphics, mcGlobaloptim, methods,
Packaged: 2021-12-08 12:24:45 UTC; Utilisateur

Packaged: 2021-12-16 08:44:59 UTC; Utilisateur

Packaged: 2022-02-15 18:49:21 UTC; Utilisateur

Packaged: 2022-01-10 12:33:26 UTC; Utilisateur

Description: Econometric methods for mixed frequency time series data analysis
Author: Virmantas Kvedaras <virmantas.kvedaras@mif.vu.lt>, Vaidotas Zemlys
Collate: 'simulate.R' 'midasr-package.R' 'midasreg.R' 'deriv.R'

Depends: R (>= 2.11.0), sandwich, optimx

Description: Methods and tools for mixed frequency time series data analysis. Allows estimation, model selection and forecasting for MIDAS regressions.
Imports: MASS, numDeriv, Matrix, forecast

Imports: MASS, numDeriv, Matrix, forecast, stats, graphics, utils

Description: Methods and tools for mixed frequency time series data analysis.
Allows estimation, model selection and forecasting for MIDAS regressions.

Author: Virmantas Kvedaras <virmantas.kvedaras@ec.europa.eu>, Vaidotas Zemlys-Balevičius
Depends: R (>= 2.11.0), sandwich, optimx, quantreg
Imports: MASS, numDeriv, Matrix, forecast, zoo, stats, graphics, utils,
Collate: 'deriv.R' 'imidasreg.R' 'lagspec.R' 'midas_nlpr.R'

Author: Virmantas Kvedaras <virmantas.kvedaras@ec.europa.eu>, Vaidotas Zemlys-Balevicius

Title: Multiple Imputation by Distance Aided Donor Selection
Authors@R: c(person("Philipp", "Gaffert", role = c("aut","cre"),
person("Florian", "Meinfelder", role = "aut",
Description: Contains the function mice.impute.midastouch. Technically this function is to be run from within the R::mice package (van Buuren et al. 2011), type ??mice. It substitutes the method "pmm" within mice by "midastouch". The authors have shown that midastouch is superior to default pmm (see URL). Many ideas are based on Siddique / Belin 2008 (MIDAS).