Logistic Regression & Survival Analysis
... The Logistic Regression The joint effects of all explanatory variables put together on the odds is Odds = P/1-P = e α + β1X1 + β2X2 + …+βpXp Taking the logarithms of both sides Log{P/1-P} = log α+β1X1+β2X2+…+βpXp Logit P = α+β1X1+β2X2+..+βpXp The coefficients β1, β2, βp are such that the sums of th ...
... The Logistic Regression The joint effects of all explanatory variables put together on the odds is Odds = P/1-P = e α + β1X1 + β2X2 + …+βpXp Taking the logarithms of both sides Log{P/1-P} = log α+β1X1+β2X2+…+βpXp Logit P = α+β1X1+β2X2+..+βpXp The coefficients β1, β2, βp are such that the sums of th ...
A contrast between two decision rules for use with (convex) sets of
... depicted by a non-trivial, convex2 set of probability functions Γ. This setting for uncertainty is different from the canonical Bayesian decision theory of expected utility, which uses a singleton set, just one probability function to represent a decision maker’s uncertainty. Justifications for usin ...
... depicted by a non-trivial, convex2 set of probability functions Γ. This setting for uncertainty is different from the canonical Bayesian decision theory of expected utility, which uses a singleton set, just one probability function to represent a decision maker’s uncertainty. Justifications for usin ...
Marginal Utility Theory of Household Behavior
... <> To restore equilibrium the consumer must buy more clothing so that (because of
diminishing MU) MUc falls. If the price of clothing is cut in half,
consumption of clothing must rise (and possibly consumption of
other commodities must fall) unti ...
... <
Prof. Halpern's notes
... Theorem: (Anscombe-Aumann) If A1–A5 hold, then there exist a utility u on prizes and a probability Pr on states such that can be represented by expected utility. • Can associate with each horse lottery h a random variable uh: ◦ uh(s) is the expected utility of the lottery h(s) on prizes (i.e., uh( ...
... Theorem: (Anscombe-Aumann) If A1–A5 hold, then there exist a utility u on prizes and a probability Pr on states such that can be represented by expected utility. • Can associate with each horse lottery h a random variable uh: ◦ uh(s) is the expected utility of the lottery h(s) on prizes (i.e., uh( ...
Predictive Methods and Statistical Modeling of Crash Data II
... Generalized Linear Models In the previous overheads, it was obvious how the normal distribution played an important role in estimating the coefficients and inferences of probabilistic models. Unfortunately, there are many practical situations where the normal assumption is not valid. Count data, bi ...
... Generalized Linear Models In the previous overheads, it was obvious how the normal distribution played an important role in estimating the coefficients and inferences of probabilistic models. Unfortunately, there are many practical situations where the normal assumption is not valid. Count data, bi ...
Making rating curves - the Bayesian approach
... While this gives us the form of f(a,b,σ2), it does not give us the form of f(c). We know that the stage levels are not too far above the zero-level. We’d like to code this prior info but we don’t want to use the stage measurement (using them both in the prior and the likelihood). Jeffrey’s priors co ...
... While this gives us the form of f(a,b,σ2), it does not give us the form of f(c). We know that the stage levels are not too far above the zero-level. We’d like to code this prior info but we don’t want to use the stage measurement (using them both in the prior and the likelihood). Jeffrey’s priors co ...