Parameter Estimation: Difference between revisions
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Revision as of 17:25, 29 February 2012
Parameter estimation refers to the process of using sample data (in our case times-to-failure or suceess data) to estimate the parameters of the selected distribution. Several parameter estimation methods are available. This section presents an overview of the available methods used in life data analysis. More specidically we start with the relatively simple method of Probability Plotting and continues with the more sophisticated methods of Rank Regression ( or Least Squares) and Maximum Likelihood.
Parameter estimation refers to the process of using sample data (in our case times-to-failure or suceess data) to estimate the parameters of the selected distribution. Several parameter estimation methods are available. This section presents an overview of the available methods used in life data analysis. More specidically we start with the relatively simple method of Probability Plotting and continues with the more sophisticated methods of Rank Regression ( or Least Squares) and Maximum Likelihood.
Template loop detected: Template:Probability Plotting
Template loop detected: Template:Rank Regression or Least Squares Parameter Estimation
Template loop detected: Template:MLE Parameter Estimation
Template loop detected: Template:Bayesian Parameter Estimation Methods
Parameter estimation refers to the process of using sample data (in our case times-to-failure or suceess data) to estimate the parameters of the selected distribution. Several parameter estimation methods are available. This section presents an overview of the available methods used in life data analysis. More specidically we start with the relatively simple method of Probability Plotting and continues with the more sophisticated methods of Rank Regression ( or Least Squares) and Maximum Likelihood.
Template loop detected: Template:Probability Plotting
Template loop detected: Template:Rank Regression or Least Squares Parameter Estimation
Template loop detected: Template:MLE Parameter Estimation
Template loop detected: Template:Bayesian Parameter Estimation Methods
Parameter estimation refers to the process of using sample data (in our case times-to-failure or suceess data) to estimate the parameters of the selected distribution. Several parameter estimation methods are available. This section presents an overview of the available methods used in life data analysis. More specidically we start with the relatively simple method of Probability Plotting and continues with the more sophisticated methods of Rank Regression ( or Least Squares) and Maximum Likelihood.
Template loop detected: Template:Probability Plotting
Template loop detected: Template:Rank Regression or Least Squares Parameter Estimation
Template loop detected: Template:MLE Parameter Estimation
Template loop detected: Template:Bayesian Parameter Estimation Methods
Parameter estimation refers to the process of using sample data (in our case times-to-failure or suceess data) to estimate the parameters of the selected distribution. Several parameter estimation methods are available. This section presents an overview of the available methods used in life data analysis. More specidically we start with the relatively simple method of Probability Plotting and continues with the more sophisticated methods of Rank Regression ( or Least Squares) and Maximum Likelihood.
Template loop detected: Template:Probability Plotting
Template loop detected: Template:Rank Regression or Least Squares Parameter Estimation
Template loop detected: Template:MLE Parameter Estimation
Template loop detected: Template:Bayesian Parameter Estimation Methods