Difference between revisions of "ANLY482 AY2016-17 T2 Group21 : Finals"
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Due to the censored demand identified during our exploratory analysis, using survival analysis provides a way for us to handle such hidden values. | Due to the censored demand identified during our exploratory analysis, using survival analysis provides a way for us to handle such hidden values. | ||
Survival analysis will be performed using the JMP built-in survival functions. We will be using two features: | Survival analysis will be performed using the JMP built-in survival functions. We will be using two features: | ||
| − | Basic survival function | + | 1. Basic survival function |
| − | Applies Kaplan-Meier estimator to account for censored values | + | - Applies Kaplan-Meier estimator to account for censored values |
| − | + | 2. (Cox) proportional hazards fit | |
| − | Fits a linear model between predictors (explanatory variables) and the hazard function. | + | - Fits a linear model between predictors (explanatory variables) and the hazard function. |
Parameters estimates show how predictors affect the hazard function. | Parameters estimates show how predictors affect the hazard function. | ||
Revision as of 17:21, 23 April 2017
| Exploratory | Mid-Term | Finals |
|---|
Finals
Survival Analysis
Due to the censored demand identified during our exploratory analysis, using survival analysis provides a way for us to handle such hidden values. Survival analysis will be performed using the JMP built-in survival functions. We will be using two features: 1. Basic survival function - Applies Kaplan-Meier estimator to account for censored values 2. (Cox) proportional hazards fit - Fits a linear model between predictors (explanatory variables) and the hazard function. Parameters estimates show how predictors affect the hazard function.
