Extracts log probabilities of empirical likelihood from a model.
Usage
# S4 method for class 'EL'
logProb(object, ...)
# S4 method for class 'ELT'
logProb(object, ...)Examples
data("precip")
fit <- el_mean(precip, par = 40)
logProb(fit)
#> Mobile Juneau Phoenix Little Rock
#> -2.966226 -3.748590 -4.881451 -3.990394
#> Los Angeles Sacramento San Francisco Denver
#> -4.776668 -4.724847 -4.664914 -4.792326
#> Hartford Wilmington Washington Jacksonville
#> -4.153093 -4.243128 -4.277509 -3.757376
#> Miami Atlanta Honolulu Boise
#> -3.493682 -3.997299 -4.625315 -4.815363
#> Chicago Peoria Indianapolis Des Moines
#> -4.388145 -4.371719 -4.282695 -4.468608
#> Wichita Louisville New Orleans Portland
#> -4.472894 -4.161886 -3.651361 -4.226853
#> Baltimore Boston Detroit Sault Ste. Marie
#> -4.199123 -4.179245 -4.464303 -4.449091
#> Duluth Minneapolis/St Paul Jackson Kansas City
#> -4.481410 -4.568660 -3.965845 -4.325723
#> St Louis Great Falls Omaha Reno
#> -4.352609 -4.760760 -4.481410 -4.878605
#> Concord Atlantic City Albuquerque Albany
#> -4.345348 -4.089271 -4.870017 -4.411153
#> Buffalo New York Charlotte Raleigh
#> -4.347774 -4.243128 -4.173492 -4.179245
#> Bismark Cincinnati Cleveland Columbus
#> -4.741331 -4.274906 -4.374082 -4.325723
#> Oklahoma City Portland Philadelphia Pittsburg
#> -4.455639 -4.310747 -4.251168 -4.345348
#> Providence Columbia Sioux Falls Memphis
#> -4.170603 -4.060621 -4.591709 -3.969389
#> Nashville Dallas El Paso Houston
#> -4.073456 -4.352609 -4.870017 -4.000733
#> Salt Lake City Burlington Norfolk Richmond
#> -4.757548 -4.431417 -4.114067 -4.176373
#> Seattle Tacoma Spokane Charleston Milwaukee
#> -4.280106 -4.721517 -4.226853 -4.504465
#> Cheyenne San Juan
#> -4.767154 -3.527270