summaryMLE: Summary the Maximum-Likelihood Estimation with the Inverse...

Description Usage Arguments Value Author(s) See Also Examples

Description

Summary the maximum-likelihood estimation including standard errors and t-values.

Usage

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## S3 method for class 'MLE'
summary(object, ...)
## S3 method for class 'mult.MLE'
summary(object, ...)

Arguments

object

object of class 'MLE' or of class 'mult.MLE', usually a result from maximum-likelihood estimation.

...

currently not used.

Value

summary.MLE returns an object of class 'summary.MLE' with the following components:

parameters

names of parameters used in the estimation procedure.

type

type of maximisation.

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.

summary.mult.MLE returns a list of class 'summary.mult.MLE' with components of class 'summary.MLE'.

Author(s)

Carter Davis, carterdavis@byu.edu

See Also

the maxLik CRAN package

Examples

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### Showing how to fit a simple vector of data to the inverse 
### hyperbolic sine distribution. 
require(graphics)
require(stats)
set.seed(123456)
x = rnorm(100)
X.f = X ~ x
start = list(mu = 0, sigma = 2, lambda = 0, k = 1)
result = ihs.mle(X.f = X.f, start = start)
sumResult = summary(result)
print(result)
coef(result)
print(sumResult)

### Comparing the fit
xvals = seq(-5, 5, by = 0.05)
coefs = coef(result)
mu = coefs[1]
sigma = coefs[2]
lambda = coefs[3]
k = coefs[4]
plot(xvals, dnorm(xvals), type = "l", col = "blue")
lines(xvals, dihs(xvals, mu = mu, sigma = sigma, 
lambda = lambda, k = k), col = "red")

Example output

Loading required package: maxLik
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/
Warning messages:
1: In log(k) : NaNs produced
2: In log(k) : NaNs produced
Maximum Likelihood estimation
BFGS maximization, 73 iterations
Return code 0: successful convergence 
Log-Likelihood: -140.6543 (4 free parameter(s))
Estimate(s): 0.01679615 0.9893086 -0.7061181 14.32567 
[1]  0.01679615  0.98930857 -0.70611810 14.32567428
--------------------------------------------
Maximum Likelihood estimation
BFGS maximization, 73 iterations
Return code 0: successful convergence 
Log-Likelihood: -140.6543
4 free parameters
Estimates:
  Parameters Estimate Std. error t value   Pr(> t)
1         mu   0.0168    0.09897  0.1697 8.652e-01
2      sigma   0.9893    0.07119 13.8977 6.541e-44
3     lambda  -0.7061    3.00496 -0.2350 8.142e-01
4          k  14.3257    4.19566  3.4144 6.392e-04
--------------------------------------------

ihs documentation built on May 2, 2019, 3:50 p.m.

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