# maximum likelihood estimation in R

I want to find ML estimates of a model using mle2 in bbmle package. When I insert new parameters (for new covariates) in model the log-likelihood value does not change and the estimated value is exactly the initial value that I determined. What's the problem? This is the code and the result:

    library(GB2)
library(bbmle)

lgb1=function(a,b0,b2,b3,b4,p,q){
xb=b0+b2*fsex1[,2]+b3*fvtype1[,2]+b4*fvuse1[,2]
ll=sum(log(dgb2(loss1,a,exp(xb),p,q)))
return(-ll)
}

start=list(a=3.1,b0=2.5,
b2=.2,b3=1,b4=-.5,
p=7.2,q=.3)

mle2(lgb1,start)->fit1
summary(fit1)
Maximum likelihood estimation

Call:
mle2(minuslogl = lgb1, start = start)

Coefficients:
Estimate  Std. Error     z value     Pr(z)
a   3.0747e+00  6.4741e-01  4.7492e+00 2.042e-06 ***
b0  2.5327e+00  4.6887e-01  5.4016e+00 6.605e-08 ***
b2  2.0000e-01  3.9686e-11  5.0396e+09 < 2.2e-16 ***
b3  1.0000e+00  7.6565e-12  1.3061e+11 < 2.2e-16 ***
b4 -5.0000e-01  1.5312e-11 -3.2653e+10 < 2.2e-16 ***
p   7.1281e+00  8.0269e+00  8.8800e-01    0.3745
q   3.5098e-01  8.6902e-02  4.0388e+00 5.372e-05 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

-2 log L: 10137.56


As you see the estimated values for b2 , b3 and b4 are the initial values of them. The log-likelihood value did not change!

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