Parameter Estimation: Difference between revisions
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==Parameter Estimation== | ==Parameter Estimation== | ||
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 | 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]]. | ||
Revision as of 13:05, 29 October 2011
Parameter Estimation
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
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
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
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
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