summary.maxLik: summary the Maximum-Likelihood estimation

In maxLik: Maximum Likelihood Estimation and Related Tools

Description

Summary the Maximum-Likelihood estimation including standard errors and t-values.

Usage

## S3 method for class 'maxLik'
summary(object, eigentol=1e-12, ... )
## S3 method for class 'summary.maxLik'
coef(object, ...)

Arguments

object	object of class 'maxLik', or 'summary.maxLik', usually a result from Maximum-Likelihood estimation.
eigentol	The standard errors are only calculated if the ratio of the smallest and largest eigenvalue of the Hessian matrix is less than “eigentol”. Otherwise the Hessian is treated as singular.
...	currently not used.

Value

An object of class 'summary.maxLik' with following components:

type

type of maximization.

iterations

number of iterations.

code

code of success.

message

a short message describing the code.

loglik

the loglik value in the maximum.

estimate

numeric matrix, the first column contains the parameter estimates, the second the standard errors, third t-values and fourth corresponding probabilities.

fixed

logical vector, which parameters are treated as constants.

NActivePar

number of free parameters.

constraints

information about the constrained optimization. Passed directly further from maxim-object. NULL if unconstrained maximization.

Author(s)

Ott Toomet, Arne Henningsen

See Also

maxLik

Examples

## ML estimation of exponential distribution:
t <- rexp(100, 2)
loglik <- function(theta) log(theta) - theta*t
gradlik <- function(theta) 1/theta - t
hesslik <- function(theta) -100/theta^2
## Estimate with numeric gradient and hessian
a <- maxLik(loglik, start=1, control=list(printLevel=2))
summary(a)
## Estimate with analytic gradient and hessian
a <- maxLik(loglik, gradlik, hesslik, start=1, control=list(printLevel=2))
summary(a)

Example output

Loading required package: miscTools

Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.

If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
----- Initial parameters: -----
fcn value: -58.17144 
     parameter initial gradient free
[1,]         1         41.82856    1
Condition number of the (active) hessian: 1 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
-----Iteration 4 -----
-----Iteration 5 -----
--------------
gradient close to zero (gradtol) 
5  iterations
estimate: 1.719057 
Function value: -45.82244 
--------------------------------------------
Maximum Likelihood estimation
Newton-Raphson maximisation, 5 iterations
Return code 1: gradient close to zero (gradtol)
Log-Likelihood: -45.82244 
1  free parameters
Estimates:
     Estimate Std. error t value Pr(> t)    
[1,]   1.7191     0.1719      10  <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
--------------------------------------------
----- Initial parameters: -----
fcn value: -58.17144 
     parameter initial gradient free
[1,]         1         41.82856    1
Condition number of the (active) hessian: 1 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
-----Iteration 4 -----
-----Iteration 5 -----
--------------
gradient close to zero (gradtol) 
5  iterations
estimate: 1.719057 
Function value: -45.82244 
--------------------------------------------
Maximum Likelihood estimation
Newton-Raphson maximisation, 5 iterations
Return code 1: gradient close to zero (gradtol)
Log-Likelihood: -45.82244 
1  free parameters
Estimates:
     Estimate Std. error t value Pr(> t)    
[1,]   1.7191     0.1719      10  <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
--------------------------------------------

maxLik documentation built on Nov. 25, 2020, 3 a.m.