Description Usage Arguments Details Author(s) Examples
View source: R/frame_ald_weight.R
This function calulate the weighting matrix
1 | frame_ald_weight(y, x, tau, error, iter)
|
y |
dependent variable of quantile regression |
x |
design matrix of quantile regression |
tau |
quantile must be a scaler |
error |
The EM algorithm accuracy of error used in MLE estimation |
iter |
The iteration frequancy for EM algorithm used in MLE estimation |
In the estimation procedure in EM algorithm, we can see that \varepsilon is inversely proportional to d_i = |y_i-x^{'}_{i}β^{(k)}_{p}|/σ. Hence, u_i(θ^{k})=\varepsilon_{-1i}(θ^{(k)}) can be interpreted as a type of weight for ith case in the estimates of β_{(k)^p}, which tends to be small for outlying observations.
Wenjing Wang wenjingwangr@gmail.com
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