Preetam Pal
2016-Jan-26 18:26 UTC
[R] Weighted Quantile Regression as a function of Tau and Weights array
I have a dataset (attached) on numeric variables y, gdp, hpa and fx. I intend to perform weighted quantile regression on this data set (i.e. y on the remaining variables) and extract the estimated coefficients. I want to do this as a bivariate function of the quantile tau and the weights array. Can you help me with how to write the function and also how to invoke it? This might be very basic, but I have very limited exposure to coding, hence any help would be really appreciated. Regards, Preetam [[alternative HTML version deleted]]
Preetam Pal
2016-Jan-26 19:45 UTC
[R] Weighted Quantile Regression as a function of Tau and Weights array
Sorry, forgot to attach the data. On Tue, Jan 26, 2016 at 11:56 PM, Preetam Pal <lordpreetam at gmail.com> wrote:> I have a dataset (attached) on numeric variables y, gdp, hpa and fx. I > intend to perform weighted quantile regression on this data set (i.e. y on > the remaining variables) and extract the estimated coefficients. I want to > do this as a bivariate function of the quantile tau and the weights array. > Can you help me with how to write the function and also how to invoke it? > This might be very basic, but I have very limited exposure to coding, hence > any help would be really appreciated. > Regards, > Preetam >-- Preetam Pal (+91)-9432212774 M-Stat 2nd Year, Room No. N-114 Statistics Division, C.V.Raman Hall Indian Statistical Institute, B.H.O.S. Kolkata. -------------- next part -------------- GDP HPA FX Y 0.514662421 0.635997077 1.37802145 1.773342598 0.936722 3.127683176 1.391916535 3.709809052 0.101482324 1.270555421 0.831157511 0.226267793 0.017548634 2.456061547 1.003945759 9.510258161 0.236462416 0.988324147 0.223682679 5.026671536 0.372005149 2.177631629 0.904226065 4.219235789 0.153915709 4.620341653 0.033410743 3.17396006 0.524887329 1.050861084 0.518201484 7.950098612 0.776616937 0.503349512 0.666089868 3.320938471 0.760074361 3.635853456 0.470220952 6.380945175 0.802986662 1.260738545 0.452674872 1.036040804 0.375145127 0.20035625 1.837306306 6.486871565 0.002568896 3.532359526 0.556752154 8.536594244 0.754309276 3.952381767 0.247402168 8.559081716 0.585966577 4.01463047 1.184382133 0.148121669 0.39767356 1.553753452 0.983129422 5.378373676 0.859898623 4.73191381 0.828795696 3.367809329 0.741376169 4.993350692 1.758051281 5.516460988 0.329240391 3.465836416 1.701655508 1.249497907 0.078661064 3.298298811 0.04575857 5.132921426 0.270971873 0.46627043 1.739487411 4.94697541 0.731072625 0.940642982 0.728747166 7.583041122 0.385038046 3.51048946 0.021866584 7.361148458 0.530760376 1.204422978 0.415530715 1.163503483 0.555323667 4.777712592 1.844184811 8.596644394