Statistics related functions
Statistics related functions
(collect-by f samples)
calculates contribution to log marginal by value;
calculates contribution to log marginal by value; - accepts a (finite) sequence of samples - returns a map containing the log sum weight weight for each unique value returned when applying f to a sample, normalized by the total number of samples
(collect-predicts k samples)
constructs a map of weighted predict values
constructs a map of weighted predict values - accepts a key and a (finite) sequence of samples - returns a map {v log-w} containing an entry v for each unique predict value with key k, along with its log sum weight normalized by the total number of samples
(collect-results samples)
constructs a map of weighted result values
constructs a map of weighted result values - accepts a (finite) sequence of samples - returns a map {v log-w} containing an entry v for each unique predict value along with its log sum weight normalized by the total number of samples
(empirical-covariance weighted)
calculates the covariance from a collection of weighted pairs [x log-w], where x may be of a number or vector.
calculates the covariance from a collection of weighted pairs [x log-w], where x may be of a number or vector.
(empirical-distribution weighted)
calculates an empirical distribution from weighted samples;
calculates an empirical distribution from weighted samples; - accepts a map or sequence of log weighted values [x log-w] - returns a map {x p} of values and normalized probabilities
(empirical-expectation f weighted)
calculates an expected value from weighted samples;
calculates an expected value from weighted samples; - accepts a function f and a map or sequence of log weighted values [x log-w]. f may return either a number or array. - returns the expected value of (f x)
(empirical-kurtosis weighted)
calculates the standardized kurtosis from a collection of weighted values [x log-w], where x may be of a number or array
calculates the standardized kurtosis from a collection of weighted values [x log-w], where x may be of a number or array
(empirical-mean weighted)
calculates the mean from a collection of weighted pairs [x log-w], where x may be of a number or array
calculates the mean from a collection of weighted pairs [x log-w], where x may be of a number or array
(empirical-skew weighted)
calculates the standardized skew from a collection of weighted values [x log-w], where x may be of a number or array
calculates the standardized skew from a collection of weighted values [x log-w], where x may be of a number or array
(empirical-std weighted)
calculates the standard deviation from a collection of weighted values [x log-w], where x may be of a number or array
calculates the standard deviation from a collection of weighted values [x log-w], where x may be of a number or array
(empirical-variance weighted)
calculates the variance from a collection of weighted pairs [x log-w], where x may be of a number or array
calculates the variance from a collection of weighted pairs [x log-w], where x may be of a number or array
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