# How to get coefficients from a model in R?

I am trying to store coefficients from a mle model just like a normally do for other models. Surprisingly, it throws an error. Any other methods to store it?

``````set.seed(111)
y.size <- rnorm(100,4,1)
p <- rnorm(100,5,1)

df <- data.frame(p, y.size)

glae <- function(A,K,Ka,q, sigma, c) {
lnqp <- if(q == 0) log(p) else ((p^q - 1)) / q
y.pred <- ((A *((p*K/Ka)-1))-1)* lnqp + c
ll <-   -sum(dnorm(y.size, mean = y.pred, sd = sigma, log=TRUE ))
ll
}

mle2.model <- mle(glae, start = list(A = -2, K = 100, Ka = 200, q= 0.1, sigma = 0.1, c=3.8))
summary(mle2.model)

Maximum likelihood estimation

Call:
``````

mle(minuslogl = glae, start = list(A = -2, K = 100, Ka = 200,
q = 0.1, sigma = 0.1, c = 3.8))

``````Coefficients:
Estimate Std. Error
A      12.511258        NaN
K      99.537509        NaN
Ka    200.231236 1684.30918
q     -32.959393        NaN
sigma 363.906677        NaN
c       8.135369   35.47982

-2 log L: 1363.185

A.final <- summary(mle2.model)\$Coefficients[1]

`Error in summary(mle2.model)\$Coefficients : \$ operator not defined for this S4 class
``````

In addition: Warning message: In sqrt(diag(object@vcov)) : NaNs produced`

### >Solution :

You can access this "mle" S4 object contents using the `@` operator, e.g.

``````library(bbmle)

set.seed(111)
y.size <- rnorm(100,4,1)
p <- rnorm(100,5,1)

df <- data.frame(p, y.size)

glae <- function(A,K,Ka,q, sigma, c) {
lnqp <- if(q == 0) log(p) else ((p^q - 1)) / q
y.pred <- ((A *((p*K/Ka)-1))-1)* lnqp + c
ll <-   -sum(dnorm(y.size, mean = y.pred, sd = sigma, log=TRUE ))
ll
}

mle2.model <- mle(glae, start = list(A = -2, K = 100, Ka = 200, q= 0.1, sigma = 0.1, c=3.8))
coefs <- mle2.model@coef
coefs
#>          A          K         Ka          q      sigma          c
#>  12.511258  99.537509 200.231236 -32.959393 363.906677   8.135369
``````

Created on 2022-05-27 by the reprex package (v2.0.1)