Could you please explain the distinction between probit and logit tails in simple terms? I'm trying to understand how they differ in terms of their behavior and what implications this has for statistical modeling and analysis. I'm particularly interested in understanding how the tails of these distributions compare and how they might impact the interpretation of results. Thank you in advance for your help.
6 answers
Chiara
Fri Oct 11 2024
The debate between Logit and Probit models in statistical analysis often arises when predicting binary outcomes. Both models are widely used in various fields, including finance and economics.
Lorenzo
Thu Oct 10 2024
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JejuJoyfulHeart
Thu Oct 10 2024
A key similarity between Logit and Probit is that they generally yield comparable results when employed for similar tasks. This similarity stems from their shared foundation in modeling the probability of a binary outcome.
charlotte_anderson_explorer
Thu Oct 10 2024
However, a notable difference lies in the underlying distributions assumed by each model. Logit models assume a logistic distribution, whereas Probit models assume a normal distribution.
Riccardo
Thu Oct 10 2024
The logistic distribution, employed in Logit models, is characterized by slightly fatter tails compared to the normal distribution. This feature can lead to slight variations in the predicted probabilities, particularly for extreme values.