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Package: statistics

Statistical estimators.

Includes nodes implementing standard statistical estimators on sample data and other (mostly frequentist) statistical procedures. This also includes a wide range of "reduction" operations such as moments, percentiles, all and any, largest and smallest that will collapse a selected axis to a single element and optionally drop the axis of same or a default type. These operations work on packets, chunks, blocks, plain arrays, and lists. Pay attention to the specific configuration of each of these nodes since a few nodes may currently default to legacy behaviors. Distribution queries such as PDF, CDF, and others are not meant to be used with the formal probability distribution classes in NeuroPype (distributions package) but instead operate on packets, plain arrays, and lists (use the nodes starting with Distribution for the latter).

Nodes in this package:

  • All (Along Axis)
    Test whether the given data has all non-zero or True values along an axis.

  • Any (Along Axis)
    Test whether the given data has any non-zero or True value along an axis.

  • Averages
    Compute multiple averages in multiple sub-ranges along an axis of interest.

  • CDF (Cumulative Distribution Function) (Basic)
    Evaluate the cumulative distribution function for a given distribution with some fixed parameters element-wise.

  • Centering
    Produce zero-mean or 'centered' data by first calculating the mean of the data and then subtracting it.

  • Centroid
    Compute a (typically robust) centroid of the given data points enumerated by an axis.

  • Correlation Coefficient
    Compute the Pearson correlation coefficient (PCC) between elements along a given axis, and average over another axis.

  • Correlation from Covariance
    Convert a covariance matrix into a matrix of correlations.

  • Average Covariance
    Compute the covariance matrix between all elements of a given axis, and average over another axis.

  • Covariance Taper Matrix
    Compute a spatial taper matrix for covariance regularization.

  • Cumulative Average
    Calculate the cumulative average of the data over time.

  • Cumulative Sum
    Calculate the cumulative sum of the data over the specified axis.

  • Curve Area
    Integrate area under the curve (AUC) using the composite trapezoidal rule of the data over a given axis.

  • Curve Length
    Compute the curve length of the data over a given axis.

  • Describe Statistical Design
    Describe the statistical design for the given data.

  • Grouped Mean
    Group instances (trials) and calculate the mean, and optionally the error, for each group.

  • Highest Density Interval
    Calculate bounds of the highest density interval along some axis, also known as the smallest credible interval or highest posterior density interval when applied to samples from a Bayesian posterior distribution.

  • Histogram
    Compute a histogram of data for each element along a given axis.

  • Largest Value / Max (Along Axis)
    Find the largest value along a given axis.

  • Linear Trend Estimation
    Calculate the linear trend over a given axis.

  • MANCOVA
    Calculate a (M)AN(C)OVA statistical model.

  • Mahalanobis Distance
    Calculate the Mahalanobis distance for some data points with respect to some mean and covariance.

  • Mean
    Compute the mean (average) over a given axis.

  • Median
    Compute the median of the data over a given axis.

  • Median Absolute Deviation
    A robust measure of the variability of some data.

  • Mixed ANOVA
    Mixed-design (split-plot) ANOVA.

  • MixedEffectsANOVA
    Linear mixed models extend standard linear models by allowing 'random' effects in addition to the standard 'fixed' effects.

  • Mode
    Compute the mode (most common value) of the data over a given axis value in the passed array.

  • Multiple Comparison Correction
    Correct p-values for multiple comparisons (multiple dependent variables).

  • Overlapped Linear Model
    Estimate a linear model with temporally overlapped responses.

  • Probability Density Function (PDF) (Basic)
    Evaluate the probability density function for a given distribution with some fixed parameters element-wise.

  • Pairwise Comparisons
    Calculate all pairwise multiple comparisons for each factor plus optional interactions using Tukey HSD.

  • Parse Stats Table
    Extract data from stats chunk returned by a stats node.

  • Per-Element Covariance
    Compute the per-element covariance matrix between elements of a given axis.

  • Percentiles
    Calculate percentiles of an array along some axis.

  • Product (Along Axis)
    Compute the product along a given axis.

  • RMANOVA
    Calculate repeated measures ANOVA.

  • Root Mean Square
    Compute the root mean square over a given axis.

  • Smallest Value / Min (Along Axis)
    Find the smallest value along a given axis.

  • Standard Deviation
    Compute the standard deviation of the data over a given axis.

  • Standardization
    Scale the data such that it is standardized.

  • Sum
    Compute the sum along a given axis.

  • T-Test
    Compute a t-test.

  • T-Test (Two Inputs)
    This node support 1-sample and 2-sample unpaired and paired t-tests.

  • Variance
    Compute the variance of the data over a given axis.

  • Winsorize
    Winsorize the given data.

  • Z-Scoring
    Produce z-scored data, that is, data with a mean of zero and a variance of one.

  • Z-Test
    Calculate a z-test.