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  2. Logit - Wikipedia

    en.wikipedia.org/wiki/Logit

    If p is a probability, then p/(1 − p) is the corresponding odds; the logit of the probability is the logarithm of the odds, i.e.: ⁡ = ⁡ = ⁡ ⁡ = ⁡ = ⁡ (). The base of the logarithm function used is of little importance in the present article, as long as it is greater than 1, but the natural logarithm with base e is the one most often used.

  3. Log probability - Wikipedia

    en.wikipedia.org/wiki/Log_probability

    In probability theory and computer science, a log probability is simply a logarithm of a probability. [1] The use of log probabilities means representing probabilities on a logarithmic scale ( − ∞ , 0 ] {\displaystyle (-\infty ,0]} , instead of the standard [ 0 , 1 ] {\displaystyle [0,1]} unit interval .

  4. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    The above formula shows that once the are fixed, we can easily compute either the log-odds that = for a given observation, or the probability that = for a given observation. The main use-case of a logistic model is to be given an observation x {\displaystyle {\boldsymbol {x}}} , and estimate the probability p ( x ) {\displaystyle p({\boldsymbol ...

  5. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    Given the independence of each event, the overall log-likelihood of intersection equals the sum of the log-likelihoods of the individual events. This is analogous to the fact that the overall log-probability is the sum of the log-probability of the individual events. In addition to the mathematical convenience from this, the adding process of ...

  6. Log5 - Wikipedia

    en.wikipedia.org/wiki/Log5

    In addition to head-to-head winning probability, a general formula can be applied to calculate head-to-head probability of outcomes such as batting average in baseball. [ 3 ] Sticking with our batting average example, let p B {\displaystyle p_{B}} be the batter 's batting average (probability of getting a hit), and let p P {\displaystyle p_{P ...

  7. Substitution matrix - Wikipedia

    en.wikipedia.org/wiki/Substitution_matrix

    We express the probabilities of transformation in what are called log-odds scores. The scores matrix S is defined as The scores matrix S is defined as S i , j = log ⁡ p i ⋅ M i , j p i ⋅ p j = log ⁡ M i , j p j = log ⁡ observed frequency expected frequency , {\displaystyle S_{i,j}=\log {\frac {p_{i}\cdot M_{i,j}}{p_{i}\cdot p_{j ...

  8. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/wiki/Multinomial_logistic...

    Suppose the odds ratio between the two is 1 : 1. Now if the option of a red bus is introduced, a person may be indifferent between a red and a blue bus, and hence may exhibit a car : blue bus : red bus odds ratio of 1 : 0.5 : 0.5, thus maintaining a 1 : 1 ratio of car : any bus while adopting a changed car : blue bus ratio of 1 : 0.5.

  9. Log-linear analysis - Wikipedia

    en.wikipedia.org/wiki/Log-linear_analysis

    Log-linear analysis is a technique used in statistics to examine the relationship between more than two categorical variables. The technique is used for both hypothesis testing and model building. In both these uses, models are tested to find the most parsimonious (i.e., least complex) model that best accounts for the variance in the observed ...