anneal
(Package: likelihood) :
Perform Simulated Annealing for Maximum Likelihood Estimation
Performs simulated annealing - a global optimization algorithm - for maximum likelihood estimation of model parameters. Bounded, unbounded, and mixed searches can all be performed. See the Simulated Annealing Algorithm help page for more on how simulated annealing is actually performed.
● Data Source:
CranContrib
● Keywords:
● Alias: anneal
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Calculate predicted results of the dependent variable from a model with parameters set up as for the likeli and anneal functions. These predicted results are useful for various statistical calculations when compared to observed results from a dataset.
● Data Source:
CranContrib
● Keywords:
● Alias: predicted_results
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write_results
(Package: likelihood) :
Write the Results of Simulated Annealing to File
Takes the results produced by the function anneal and writes them to a tab-delimited text file.
● Data Source:
CranContrib
● Keywords:
● Alias: write_results
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Wraps the function likeli so you can use it with optim. This allows you to use other optimization methods to find maximum likelihood estimates.
● Data Source:
CranContrib
● Keywords:
● Alias: likeli_4_optim
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Calculates asymptotic support limits for parameter maximum likelihood estimates. For a parameter, support limits are the values above and below the maximum likelihood estimate that cause the likelihood to drop by a given number of units, while holding all other parameters at their maximum likelihood values. Two units is standard. 1.92 units roughly corresponds to a 95% confidence interval.
● Data Source:
CranContrib
● Keywords:
● Alias: support_limits
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This gives details on how the simulated annealing process is performed.
● Data Source:
CranContrib
● Keywords:
● Alias: Simulated Annealing Algorithm
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There are four inputs to a likelihood calculation: a scientific model, a probability model, parameters for the model, and data. The scientific model mathematically describes one or more relationships that have been captured by the data. The probability model describes the error in the data. The parameters are the variables of interest for the scientific and probability models, for which you are trying to find the best values.
● Data Source:
CranContrib
● Keywords:
● Alias: Likelihood Calculation
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likeli
(Package: likelihood) :
Calculate Likelihood
Calculate likelihood of a model, given a dataset. Typically this is log likelihood. See the Likelihood Calculation page for details on how likelihood is calculated.
● Data Source:
CranContrib
● Keywords:
● Alias: likeli
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This package allows you to find the maximum likelihood estimates of statistical models using simulated annealing, a global optimization algorithm.
● Data Source:
CranContrib
● Keywords:
● Alias: likelihood, likelihood-package
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providing 
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