Difference between revisions of "ANLY482 AY2016-17 T2 Group21 : Finals"
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==<div style="background: #404041;font-weight: light; padding:0.3em; text-transform:uppercase;letter-spacing:0.1em;font-size:18px; font-family: 'Century Gothic'"><font color=#ffffff><center>Survival Analysis</center></font></div>== | ==<div style="background: #404041;font-weight: light; padding:0.3em; text-transform:uppercase;letter-spacing:0.1em;font-size:18px; font-family: 'Century Gothic'"><font color=#ffffff><center>Survival Analysis</center></font></div>== | ||
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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: |
Revision as of 17:23, 23 April 2017
Exploratory | Mid-Term | Finals |
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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.