midasr: Mixed Data Sampling Regression

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

Install the latest version of this package by entering the following in R:
AuthorVirmantas Kvedaras <virmantas.kvedaras@mif.vu.lt>, Vaidotas Zemlys <vaidotas.zemlys@mif.vu.lt>
Date of publication2016-08-08 16:52:48
MaintainerVaidotas Zemlys <zemlys@gmail.com>
LicenseGPL-2 | MIT + file LICENCE

View on CRAN

Man pages

agk.test: Andreou, Ghysels, Kourtellos LM test

almonp: Almon polynomial MIDAS weights specification

almonp_gradient: Gradient function for Almon polynomial MIDAS weights

amidas_table: Weight and lag selection table for aggregates based MIDAS...

amweights: Weights for aggregates based MIDAS regressions

average_forecast: Average forecasts of MIDAS models

check_mixfreq: Check data for MIDAS regression

coef.midas_r: Extract coefficients of MIDAS regression

deriv_tests: Check whether non-linear least squares restricted MIDAS...

deviance.midas_r: MIDAS regression model deviance

dmls: MIDAS lag structure for unit root processes

expand_amidas: Create table of weights, lags and starting values for Ghysels...

expand_weights_lags: Create table of weights, lags and starting values

fmls: Full MIDAS lag structure

forecast.midas_r: Forecast MIDAS regression

genexp: Generalized exponential MIDAS coefficients

genexp_gradient: Gradient of feneralized exponential MIDAS coefficient...

get_estimation_sample: Get the data which was used to etimate MIDAS regression

gompertzp: Normalized Gompertz probability density function MIDAS...

gompertzp_gradient: Gradient function for normalized Gompertz probability density...

hAhr_test: Test restrictions on coefficients of MIDAS regression using...

hAh_test: Test restrictions on coefficients of MIDAS regression

harstep: HAR(3)-RV model MIDAS weights specification

harstep_gradient: Gradient function for HAR(3)-RV model MIDAS weights...

hf_lags_table: Create a high frequency lag selection table for MIDAS...

imidas_r: Restricted MIDAS regression with I(1) regressors

lcauchyp: Normalized log-Cauchy probability density function MIDAS...

lcauchyp_gradient: Gradient function for normalized log-Cauchy probability...

lf_lags_table: Create a low frequency lag selection table for MIDAS...

lws_table-add: Combine 'lws_table' objects

midas_auto_sim: Simulate simple autoregressive MIDAS model

midas_r: Restricted MIDAS regression

midas_r.fit: Fit restricted MIDAS regression

midas_r_ic_table: Create a weight and lag selection table for MIDAS regression...

midas_r_np: Estimate non-parametric MIDAS regression

midasr-package: Mixed Data Sampling Regression

midas_r_simple: Restricted MIDAS regression

midas_sim: Simulate simple MIDAS regression response variable

midas_u: Estimate unrestricted MIDAS regression

mls: MIDAS lag structure

modsel: Select the model based on given information criteria

nakagamip: Normalized Nakagami probability density function MIDAS...

nakagamip_gradient: Gradient function for normalized Nakagami probability density...

nbeta: Normalized beta probability density function MIDAS weights...

nbeta_gradient: Gradient function for normalized beta probability density...

nbetaMT: Normalized beta probability density function MIDAS weights...

nbetaMT_gradient: Gradient function for normalized beta probability density...

nealmon: Normalized Exponential Almon lag MIDAS coefficients

nealmon_gradient: Gradient function for normalized exponential Almon lag...

oos_prec: Out-of-sample prediction precision data on simulation example

plot_midas_coef: Plot MIDAS coefficients

polystep: Step function specification for MIDAS weights

polystep_gradient: Gradient of step function specification for MIDAS weights

predict.midas_r: Predict method for MIDAS regression fit

prep_hAh: Calculate data for hAh_test and hAhr_test

rvsp500: Realized volatility of S&P500 index

select_and_forecast: Create table for different forecast horizons

simulate.midas_r: Simulate MIDAS regression response

split_data: Split mixed frequency data into in-sample and out-of-sample

update_weights: Updates weights in MIDAS regression formula

USpayems: United States total employment non-farms payroll, monthly,...

USqgdp: United States gross domestic product, quarterly, seasonaly...

USrealgdp: US annual gross domestic product in billions of chained 2005...

USunempr: US monthly unemployment rate

weights_table: Create a weight function selection table for MIDAS regression...


agk.test Man page
almonp Man page
almonp_gradient Man page
amidas_table Man page
amweights Man page
average_forecast Man page
check_mixfreq Man page
coef.midas_r Man page
deriv_tests Man page
deriv_tests.midas_r Man page
deviance.midas_r Man page
dmls Man page
expand_amidas Man page
expand_weights_lags Man page
fmls Man page
forecast Man page
forecast.midas_r Man page
genexp Man page
genexp_gradient Man page
get_estimation_sample Man page
gompertzp Man page
gompertzp_gradient Man page
hAhr_test Man page
hAh_test Man page
harstep Man page
harstep_gradient Man page
hf_lags_table Man page
imidas_r Man page
lcauchyp Man page
lcauchyp_gradient Man page
lf_lags_table Man page
+.lws_table Man page
midas_auto_sim Man page
midasr Man page
midas_r Man page
midas_r.fit Man page
midas_r_ic_table Man page
midas_r_np Man page
midasr-package Man page
midas_r_simple Man page
midas_sim Man page
midas_u Man page
mls Man page
modsel Man page
nakagamip Man page
nakagamip_gradient Man page
nbeta Man page
nbeta_gradient Man page
nbetaMT Man page
nbetaMT_gradient Man page
nealmon Man page
nealmon_gradient Man page
oos_prec Man page
plot_midas_coef Man page
polystep Man page
polystep_gradient Man page
predict.midas_r Man page
prep_hAh Man page
rvsp500 Man page
select_and_forecast Man page
simulate Man page
simulate.midas_r Man page
split_data Man page
update_weights Man page
USpayems Man page
USqgdp Man page
USrealgdp Man page
USunempr Man page
weights_table Man page


tests/testthat/test_midaslag.R tests/testthat/test_methods.R tests/testthat/test_midasr.R
demo/logRV.R demo/autoreg.R demo/okun.R demo/RV.R demo/imidasr.R
R/nonparametric.R R/midasr-package.R R/midasreg.R R/midaslag.R R/lagspec.R R/midas_r_methods.R R/simulate.R R/deriv.R R/imidasreg.R R/modsel.R R/tests.R
man/deriv_tests.Rd man/midas_auto_sim.Rd man/USqgdp.Rd man/prep_hAh.Rd man/hAh_test.Rd man/coef.midas_r.Rd man/nbetaMT_gradient.Rd man/USpayems.Rd man/mls.Rd man/midas_r_simple.Rd man/amidas_table.Rd man/expand_amidas.Rd man/simulate.midas_r.Rd man/fmls.Rd man/midas_u.Rd man/oos_prec.Rd man/rvsp500.Rd man/plot_midas_coef.Rd man/lws_table-add.Rd man/midas_r_ic_table.Rd man/genexp.Rd man/modsel.Rd man/polystep.Rd man/USunempr.Rd man/forecast.midas_r.Rd man/select_and_forecast.Rd man/midas_r_np.Rd man/almonp_gradient.Rd man/amweights.Rd man/almonp.Rd man/midas_r.fit.Rd man/nakagamip.Rd man/nbeta_gradient.Rd man/nealmon.Rd man/polystep_gradient.Rd man/harstep.Rd man/gompertzp_gradient.Rd man/USrealgdp.Rd man/nakagamip_gradient.Rd man/dmls.Rd man/check_mixfreq.Rd man/gompertzp.Rd man/update_weights.Rd man/hAhr_test.Rd man/imidas_r.Rd man/average_forecast.Rd man/agk.test.Rd man/lcauchyp_gradient.Rd man/lcauchyp.Rd man/midasr-package.Rd man/nealmon_gradient.Rd man/midas_sim.Rd man/lf_lags_table.Rd man/midas_r.Rd man/harstep_gradient.Rd man/deviance.midas_r.Rd man/hf_lags_table.Rd man/split_data.Rd man/get_estimation_sample.Rd man/genexp_gradient.Rd man/expand_weights_lags.Rd man/predict.midas_r.Rd man/nbeta.Rd man/nbetaMT.Rd man/weights_table.Rd

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