Analytics Toolbox for Redshift

Code

statistics

This module contains functions to perform spatial statistics calculations.

GETIS_ORD_QUADBIN

Description

This function computes the Getis-Ord Gi* statistic for each quadbin index in the input array.

input: SUPER input data with the indexes and values of the cells.
size: INT8 size of the quadbin kring (distance from the origin). This defines the area around each index cell that will be taken into account to compute its Gi* statistic.
kernel: VARCHAR kernel function to compute the spatial weights across the kring. Available functions are: uniform, triangular, quadratic, quartic and gaussian.

Return type

SUPER

Example

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SELECT carto.GETIS_ORD_QUADBIN(
    JSON_PARSE('[
        {"index": 5266443791933898751, "value": 51.0},
        {"index": 5266443803500740607, "value": 28.0},
        {"index": 5266443790415822847, "value": 19.0}
    ]'),
    3, 'gaussian'
);
-- [{"index":5266443791933898751,"gi":1.3606194139870578,"p_value":0.086817058065399522},{"index":5266443803500740607,"gi":-0.34633948719670504,"p_value":0.63545613599515272},{"index":5266443790415822847,"gi":-1.0142799267903513,"p_value":0.84477538488255133}]

MORANS_I_QUADBIN

Description

This function computes the Moran’s I spatial autocorrelation from the input array of quadkey indexes.

input: SUPER input data with the indexes and values of the cells.
size: INT8 size of the quadkey kring (distance from the origin). This defines the area around each index cell where the distance decay will be applied.
decay: VARCHAR decay function to compute the distance decay. Available functions are: uniform, inverse, inverse_square and exponential.

Return type

FLOAT8

Example

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SELECT carto.MORANS_I_QUADBIN(
    JSON_PARSE('[
        {"index": 5266443791927869439, "value": 51.0},
        {"index": 5266443791928131583, "value": 28.0},
        {"index": 5266443791928918015, "value": 19.0}
    ]'),
    3, 'exponential'
);
-- -0.2966571382680862

P_VALUE

Description

This function computes the one tail p-value (upper-tail test) of a given z-score assuming the population follows a normal distribution where the mean is 0 and the standard deviation is 1. The z-score is a measure of how many standard deviations below or above the population mean a value is. It gives you an idea of how far from the mean a data point is. The p-value is the probability that a randomly sampled point has a value at least as extreme as the point whose z-score is being tested.

z_score: FLOAT8 input data with the indexes and values of the cells.

Return type

FLOAT8

Example

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SELECT carto.P_VALUE(-2);
-- 0.9772499371127437