August 2013
Intermediate to advanced
195 pages
5h 45m
English
Content preview from Nonparametric Methods in Statistics with SAS Applications
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112 NONPARAMETRIC GENERALIZED ADDITIVE REGRESSION
dist=poisson;
output out=result pred;
run;
proc print data=result;
run;
SAS outputs the fitted parameters and the estimated spline.
Parameter
Parameter Estimate Pr > |t|
Intercept 2.33372 <.0001
Linear(temp) 0.00825 0.4978
Linear(rainfall) -0.04015 0.0295
Source Pr > ChiSq
Spline(temp) 0.0413
Spline(rainfall) 0.2537
Obs temp rainfall n_mice P_n_mice P_temp P_rainfall
1 -10 36.4 1 1.14397 -0.45938 -0.19567
2 10 27.1 0 3.15302 -0.17688 -0.00281
3 -20 43.3 0 0.15952 -0.88315 -1.38237
4 -9 32.9 1 2.10108 -0.38721 0.19132
5 14 25.5 2 2.53926 -0.35816 -0.13527
--- lines omitted ---
16 5 14.2 9 8.79123 0.28791 0.08106
17
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