Example MIDAS dataset

This dataset contains simulated high-frequency covariates and a binomial response constructed using MIDAS lag weights.

Usage

data_binomial_example

Format

A list with the following components:

x1

Numeric vector of high-frequency covariate 1

x2

Numeric vector of high-frequency covariate 2

y

Integer vector of binomial response counts

p

Underlying success probabilities

Ntrials

Number of trials for each observation

weights1

Lag weights used in the MIDAS structure for covariate 1

weights2

Lag weights used in the MIDAS structure for covariate 2

beta0

True value of intercept \(\beta_0\)

beta1

True value of \(\beta_1\)

beta2

True value of \(\beta_2\)

beta3

True value of \(\beta_3\)

Source

Simulated data

Details

Simulated dataset generated using a binomial sampling model

The dataset is generated using two covariates. The first one has a hyperbolic weighting scheme with parameter gamma = 0.9 and lag length 13. The second one has gaussian weighting scheme with parameters mu = 8, sigma = 7, and lag length of 20.