midasr0.8 package

Mixed Data Sampling Regression

midas_sim

Simulate simple MIDAS regression response variable

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 regression m...

amweights

Weights for aggregates based MIDAS regressions

average_forecast

Average forecasts of MIDAS models

check_mixfreq

Check data for MIDAS regression

coef.midas_nlpr

Extract coefficients of MIDAS regression

coef.midas_r

Extract coefficients of MIDAS regression

coef.midas_sp

Extract coefficients of MIDAS regression

deriv_tests

Check whether non-linear least squares restricted MIDAS regression pro...

deviance.midas_nlpr

Non-linear parametric MIDAS regression model deviance

deviance.midas_r

MIDAS regression model deviance

deviance.midas_sp

Semi-parametric MIDAS regression model deviance

dmls

MIDAS lag structure for unit root processes

expand_amidas

Create table of weights, lags and starting values for Ghysels weight s...

expand_weights_lags

Create table of weights, lags and starting values

extract.midas_r

Extract coefficients and GOF measures from MIDAS regression object

fitted.midas_nlpr

Fitted values for non-linear parametric MIDAS regression model

fitted.midas_sp

Fitted values for semi-parametric MIDAS regression model

fmls

Full MIDAS lag structure

forecast.midas_r

Forecast MIDAS regression

genexp

Generalized exponential MIDAS coefficients

genexp_gradient

Gradient of generalized exponential MIDAS coefficient generating funct...

get_estimation_sample

Get the data which was used to etimate MIDAS regression

gompertzp

Normalized Gompertz probability density function MIDAS weights specifi...

gompertzp_gradient

Gradient function for normalized Gompertz probability density function...

hAh_test

Test restrictions on coefficients of MIDAS regression

hAhr_test

Test restrictions on coefficients of MIDAS regression using robust ver...

harstep

HAR(3)-RV model MIDAS weights specification

harstep_gradient

Gradient function for HAR(3)-RV model MIDAS weights specification

hf_lags_table

Create a high frequency lag selection table for MIDAS regression model

imidas_r

Restricted MIDAS regression with I(1) regressors

lcauchyp

Normalized log-Cauchy probability density function MIDAS weights speci...

lcauchyp_gradient

Gradient function for normalized log-Cauchy probability density functi...

lf_lags_table

Create a low frequency lag selection table for MIDAS regression model

lstr

Compute LSTR term for high frequency variable

lws_table-add

Combine lws_table objects

midas_auto_sim

Simulate simple autoregressive MIDAS model

midas_lstr_plain

LSTR (Logistic Smooth TRansition) MIDAS regression

midas_lstr_sim

Simulate LSTR MIDAS regression model

midas_mmm_plain

MMM (Mean-Min-Max) MIDAS regression

midas_mmm_sim

Simulate MMM MIDAS regression model

midas_nlpr.fit

Fit restricted MIDAS regression

midas_nlpr

Non-linear parametric MIDAS regression

midas_pl_plain

MIDAS Partialy linear non-parametric regression

midas_pl_sim

Simulate PL MIDAS regression model

midas_qr

Restricted MIDAS quantile regression

midas_r.fit

Fit restricted MIDAS regression

midas_r

Restricted MIDAS regression

midas_r_ic_table

Create a weight and lag selection table for MIDAS regression model

midas_r_np

Estimate non-parametric MIDAS regression

midas_r_plain

Restricted MIDAS regression

midas_si_plain

MIDAS Single index regression

midas_si_sim

Simulate SI MIDAS regression model

midas_sp

Semi-parametric MIDAS regression

midas_u

Estimate unrestricted MIDAS regression

midasr-package

Mixed Data Sampling Regression

mls

MIDAS lag structure

mlsd

MIDAS lag structure with dates

mmm

Compute MMM term for high frequency variable

modsel

Select the model based on given information criteria

nakagamip

Normalized Nakagami probability density function MIDAS weights specifi...

nakagamip_gradient

Gradient function for normalized Nakagami probability density function...

nbeta

Normalized beta probability density function MIDAS weights specificati...

nbeta_gradient

Gradient function for normalized beta probability density function MID...

nbetaMT

Normalized beta probability density function MIDAS weights specificati...

nbetaMT_gradient

Gradient function for normalized beta probability density function MID...

nealmon

Normalized Exponential Almon lag MIDAS coefficients

nealmon_gradient

Gradient function for normalized exponential Almon lag weights

plot_lstr

Plot MIDAS coefficients

plot_midas_coef.midas_nlpr

Plot MIDAS coefficients

plot_midas_coef.midas_r

Plot MIDAS coefficients

plot_sp

Plot non-parametric part of the single index MIDAS regression

polystep

Step function specification for MIDAS weights

polystep_gradient

Gradient of step function specification for MIDAS weights

predict.midas_nlpr

Predict method for non-linear parametric MIDAS regression fit

predict.midas_r

Predict method for MIDAS regression fit

predict.midas_sp

Predict method for semi-parametric MIDAS regression fit

prep_hAh

Calculate data for hAh_test and hAhr_test

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

weights_table

Create a weight function selection table for MIDAS regression model

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

  • Maintainer: Vaidotas Zemlys-Balevičius
  • License: GPL-2 | MIT + file LICENCE
  • Last published: 2021-02-23