# infactor_or1: Inefficiency factor for ordinal quantile model with more than... In bqror: Bayesian Quantile Regression for Ordinal Models

## Description

This function calculates the inefficiency factor from the MCMC draws of (β, δ) for ordinal quantile model with more than 3 outcomes. The inefficiency factor is calculated using the batch-means method.

## Usage

 `1` ```infactor_or1(x, beta, delta, autocorrelationCutoff) ```

## Arguments

 `x` covariate matrix of dimension (n x k) including a column of ones with or without column names. `beta` Gibbs draw of coefficients of dimension (k x nsim). `delta` Gibbs draw of cut-points. `autocorrelationCutoff` cut-off to identify the number of lags.

## Details

Calculates the inefficiency factor of (β, δ) using the batch-means method.

## Value

Returns a list with components

• `inefficiencyDelta`: vector with inefficiency factor for each δ.

• `inefficiencyBeta`: vector with inefficiency factor for each β.

## References

Greenberg, E. (2012). “Introduction to Bayesian Econometrics.” Cambridge University Press, Cambridge. DOI: 10.1017/CBO9780511808920

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```set.seed(101) data("data25j4") x <- data25j4\$x y <- data25j4\$y k <- dim(x)[2] J <- dim(as.array(unique(y)))[1] D0 <- 0.25*diag(J - 2) output <- quantreg_or1(y = y,x = x, B0 = 10*diag(k), D0 = D0, mcmc = 40, p = 0.25, tune = 1, display = FALSE) beta <- output\$beta delta <- output\$delta inefficiency <- infactor_or1(x, beta, delta, 0.5) # Summary of Inefficiency Factor: # Inefficiency # beta_0 1.1008 # beta_1 3.0024 # beta_2 2.8543 # delta_1 3.6507 # delta_2 3.1784 ```