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midasr (version 0.3)

Mixed Data Sampling Regression

Description

Econometric methods for mixed frequency time series data analysis

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Version

Install

install.packages('midasr')

Monthly Downloads

1,237

Version

0.3

License

GPL-2 | MIT + file LICENCE

Maintainer

Vaidotas Zemlys

Last Published

April 30th, 2014

Functions in midasr (0.3)

USpayems

United States total employment non-farms payroll, monthly, seasonally adjusted.

USunempr

US monthly unemployment rate

deriv_tests

Check whether non-linear least squares restricted MIDAS regression problem has converged

amidas_table

Weight and lag selection table for aggregates based MIDAS regression model

almonp

Almon polynomial MIDAS weights specification

gompertzp.gradient

Gradient function for normalized Gompertz probability density function MIDAS weights specification Calculate gradient function for normalized Gompertz probability density function specification of MIDAS weights.

checkARstar

Check whether the MIDAS model is MIDAS-AR* model

USrealgdp

US annual gross domestic product in billions of chained 2005 dollars

deviance.midas_r

MIDAS regression model deviance

midas.auto.sim

Simulate autoregressive MIDAS model

prep_hAh

Calculate data for hAh.test and hAhr.test

average_forecast

Average forecasts of MIDAS models

+.lws_table

Combine lws_table objects

imidas_r.imidas_r

Restricted MIDAS regression with I(1) regressors

weight_coef

Return the restricted coefficients generated by restriction function(s)

midas_r.midas_r

Restricted MIDAS regression

polystep.gradient

Gradient of step function specification for MIDAS weights

amweights

Weights for aggregates based MIDAS regressions

AICc

Compute AICc

imidas_r

Restricted MIDAS regression with I(1) regressors

split_data

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

weight_names

Return the names of restriction function(s)

midas_coef

Return the coefficients of MIDAS regression

almonp.gradient

Gradient function for Almon polynomial MIDAS weights

predict.midas_r

Predict method for MIDAS regression fit

hAhr.test

Test restrictions on coefficients of MIDAS regression using robust version of the test

nakagamip.gradient

Gradient function for normalized Nakagami probability density function MIDAS weights specification Calculate gradient function for normalized Nakagami probability density function specification of MIDAS weights.

midas.sim

Simulate MIDAS regression response variable

nbetaMT.gradient

Gradient function for normalized beta probability density function MIDAS weights specification (MATLAB toolbox compatible) Calculate gradient function for normalized beta probability density function specification of MIDAS weights.

midas_u

Estimate unrestricted MIDAS regression

select_and_forecast

Create table for different forecast horizons

agk.test

Andreou, Ghysels, Kourtellos LM test

polystep

Step function specification for MIDAS weights

expand_amidas

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

dmls

MIDAS lag structure for unit root processes

hAh.test

Test restrictions on coefficients of MIDAS regression

nbetaMT

Normalized beta probability density function MIDAS weights specification (MATLAB toolbox compatible) Calculate MIDAS weights according to normalized beta probability density function specification. Compatible with the specification in MATLAB toolbox.

gompertzp

Normalized Gompertz probability density function MIDAS weights specification Calculate MIDAS weights according to normalized Gompertz probability density function specification

nealmon.gradient

Gradient function for normalized exponential Almon lag weights

harstep.gradient

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

USqgdp

United States gross domestic product, quarterly, seasonaly adjusted annual rate.

modsel

Select the model based on given information criteria

fmls

Full MIDAS lag structure

expand_weights_lags

Create table of weights, lags and starting values

mls

MIDAS lag structure

harstep

HAR(3)-RV model MIDAS weights specification

midas_r_simple

Restricted MIDAS regression

check_mixfreq

Check data for MIDAS regression

get_estimation_sample

Get the data which was used to etimate MIDAS regression

lcauchyp

Normalized log-Cauchy probability density function MIDAS weights specification Calculate MIDAS weights according to normalized log-Cauchy probability density function specification

midas_r.fit

Fit restricted MIDAS regression

midas_r

Restricted MIDAS regression

lcauchyp.gradient

Gradient function for normalized log-Cauchy probability density function MIDAS weights specification Calculate gradient function for normalized log-Cauchy probability density function specification of MIDAS weights.

midas_r_np

Estimate non-parametric MIDAS regression

nbeta.gradient

Gradient function for normalized beta probability density function MIDAS weights specification Calculate gradient function for normalized beta probability density function specification of MIDAS weights.

forecast

Forecast MIDAS regression

mls_coef

Return the coefficients for fmls variables

nbeta

Normalized beta probability density function MIDAS weights specification Calculate MIDAS weights according to normalized beta probability density function specification

oos_prec

Out-of-sample prediction precision data on simulation example

weights_table

Create a weight function selection table for MIDAS regression model

hf_lags_table

Create a high frequency lag selection table for MIDAS regression model

midasr-package

Estimating and testing MIDAS regression

simplearma.sim

Simulate AR(1) or MA(1) model

lf_lags_table

Create a low frequency lag selection table for MIDAS regression model

nakagamip

Normalized Nakagami probability density function MIDAS weights specification Calculate MIDAS weights according to normalized Nakagami probability density function specification

rvsp500

Realized volatility of S&P500 index

weight_param

Return the estimated hyper parameters of the weight function(s)

midas_r_ic_table

Create a weight and lag selection table for MIDAS regression model

nealmon

Normalized Exponential Almon lag MIDAS coefficients

prepmidas_r

Prepare necessary objects for fitting of the MIDAS regression