Dear community, I would please like to ask for your help concerning the following issue. As "proc quanrteg" offers the opportunity to estimate conditional cumulative distribution functions (:= CDFs), instead of plotting a graph, I would please like to know, how to obtain the predictions for arbitrary values on the plot's abscissa, i.e., nothing else but predicted values for the CDF(x), Example: 1. First, I would like to use "proc quantreg" to fit the model. Say, on a sample of N_1 = 1000 observations, with dependent variable y and independent variables x1 and x2. 2. Second, I would like to use the fitted model from step one, to get estimated for a new sample of N_2 = 100 new observations, for which I observe x_1 and x_2; assume, I am interested, for each observation, in the estimated value for CDF(7) (i.e., the probability, that y is smaller-or-equal to -1) , CDF(11), and CDF(13). The beginnings for the example follow. I would be very glad if you were to provide help for this question of mine, please. Yours sincerely, Sinistrum data pro_fit;
seed = 1;
call streaminit(seed);
do i = 1 to 1000;
x1 = rand ('normal', 10, 2);
x2 = rand ('normal', 5, 1);
y1 = 1 + 2 * x1 + 5 * x2 + rand ('normal', 0, 0.5);
output;
end;
drop seed;
run;
data pro_predict;
seed = 2;
call streaminit(seed);
do i = 1 to 100;
x1 = rand ('normal', 10, 2);
x2 = rand ('normal', 5, 1);
output;
end;
drop seed;
run;
proc quantreg
data = pro_fit
ci = none;
model
y1 = x1 x2;
conddist
plot = (
cdfplot
pdfplot
)
;
run;
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