[R] about error while using anova function

[narendarreddy kalam]

fit1<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc)
fit2<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.5,data=wbc)
fit3<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc)
fit4<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc)
fit5<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc)
*output of tau=0.15*fit1
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


*output of tau=0.3*fit2
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

*output of tau=0.5*fit3
Call:
rq(formula = op ~ inp1 + inp2 + inp3 + inp4 + inp5 + inp6 + inp7 + 
    inp8 + inp9, tau = 0.5, data = wbc)

Coefficients:
  (Intercept)          inp1          inp2          inp3          inp4 
-1.400000e-01  5.810236e-17  4.000000e-02  1.087160e-16  4.297771e-18 
         inp5          inp6          inp7          inp8          inp9 
 8.045868e-17  8.000000e-02  6.841101e-17  2.000000e-02  7.560947e-17 

Degrees of freedom: 673 total; 663 residual
*output of tau=0.65*
Call:
rq(formula = op ~ inp1 + inp2 + inp3 + inp4 + inp5 + inp6 + inp7 + 
    inp8 + inp9, tau = 0.65, data = wbc)

Coefficients:
 (Intercept)         inp1         inp2         inp3         inp4        
inp5 
-0.193593706  0.005012804  0.044208182  0.008994346  0.006214294 
0.007622629 
        inp6         inp7         inp8         inp9 
 0.064595895  0.006214294  0.028904532  0.001775512 

Degrees of freedom: 673 total; 663 residual
*output of tau=0.9:*
fit5
Call:
rq(formula = op ~ inp1 + inp2 + inp3 + inp4 + inp5 + inp6 + inp7 + 
    inp8 + inp9, tau = 0.9, data = wbc)

Coefficients:
 (Intercept)         inp1         inp2         inp3         inp4        
inp5 
-0.249006688  0.040430238  0.010854846  0.031021326  0.013558943 
0.024867111 
        inp6         inp7         inp8         inp9 
 0.050441784  0.024867111  0.027018345  0.001079872 

Degrees of freedom: 673 total; 663 residual
<
b> so fit1 fit2,fit3,fit4,fit5 are the 5 quantiles of the wbc dataset.but
why i am encoutering the following error while using anova*

*anova(fit1,fit2,fit3,fit4,fit5);
Error in solve.default(D %*% W %*% t(D), D %*% coef) : 
  system is computationally singular: reciprocal condition number =
5.58091e-19
In addition: 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
3: In summary.rq(x, se = "nid", covariance = TRUE) : 206 non-positive fis
4: In summary.rq(x, se = "nid", covariance = TRUE) : 53 non-positive fis
5: In summary.rq(x, se = "nid", covariance = TRUE) : 30 non-positive fis*


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