# [R] about interpretation of anova results...

narendarreddy kalam narendarcse007 at gmail.com
Mon Dec 5 08:18:03 CET 2011

```quantreg package is used.
*fit1 results are*
Call:
rq(formula = op ~ inp1 + inp2 + inp3 + inp4 + inp5 + inp6 + inp7 +
inp8 + inp9, tau = 0.15, data = wbc)

Coefficients:
(Intercept)         inp1         inp2         inp3         inp4
inp5
-0.191528450  0.005276347  0.021414032  0.016034803  0.007510343
0.005276347
inp6         inp7         inp8         inp9
0.058708544  0.005224906  0.006804871 -0.003931540

Degrees of freedom: 673 total; 663 residual
*fit2 results are*
Call:
rq(formula = op ~ inp1 + inp2 + inp3 + inp4 + inp5 + inp6 + inp7 +
inp8 + inp9, tau = 0.3, data = wbc)

Coefficients:
(Intercept)          inp1          inp2          inp3          inp4
-1.111111e-01  5.776765e-19  4.635734e-18  1.874715e-18  2.099872e-18
inp5          inp6          inp7          inp8          inp9
-4.942052e-19  1.111111e-01  2.205289e-18  4.138435e-18  9.300642e-19

Degrees of freedom: 673 total; 663 residual

anova(fit1,fit2);
Quantile Regression Analysis of Deviance Table

Model: op ~ inp1 + inp2 + inp3 + inp4 + inp5 + inp6 + inp7 + inp8 + inp9
Joint Test of Equality of Slopes: tau in {  0.15 0.3  }

Df Resid Df F value Pr(>F)
1  9     1337  0.5256 0.8568
Warning messages:
1: In summary.rq(x, se = "nid", covariance = TRUE) : 93 non-positive fis
2: In summary.rq(x, se = "nid", covariance = TRUE) : 138 non-positive fis
how to interpret the above results??

what is the use of anova function??
will it give the best among fit1 && fit2..

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