nan

A statistics and machine learning toolbox for data with and w/o missing values

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A statistics and machine learning toolbox for data with and w/o missing values

coefficient_of_variation
COEFFICIENT_OF_VARIATION returns STD(X)/MEAN(X) cv=coefficient_of_variation(x [,DIM]) cv=std(x)/mean(x)
geomean
GEOMEAN calculates the geomentric mean of data elements.
meansq
MEANSQ calculates the mean of the squares
skewness
SKEWNESS estimates the skewness
covm
COVM generates covariance matrix X and Y can contain missing values encoded with NaN.
cor
COR calculates the correlation matrix X and Y can contain missing values encoded with NaN.
cov
COV covariance matrix X and Y can contain missing values encoded with NaN.
corrcoef
CORRCOEF calculates the correlation matrix from pairwise correlations.
harmmean
HARMMEAN calculates the harmonic mean of data elements.
median
MEDIAN data elements, [y]=median(x [,DIM])
statistic
STATISTIC estimates various statistics at once.
detrend
DETREND removes the trend from data, NaN's are considered as missing values DETREND is fully compatible to previous Matlab and Octave DETREND with the following features added: - handles NaN's...
kurtosis
KURTOSIS estimates the kurtosis
moment
MOMENT estimates the p-th moment M = moment(x, p [,opt] [,DIM]) M = moment(H, p [,opt]) calculates p-th central moment from data x in dimension DIM of from Histogram H
std
STD calculates the standard deviation.
mad
MAD estimates the Mean Absolute deviation (note that according to [1,2] this is the mean deviation; not the mean absolute deviation)
naninsttest
NANINSTTEST checks whether the functions from NaN-toolbox have been correctly installed.
nantest
NANTEST checks several mathematical operations and a few statistical functions for their correctness related to NaN's. e.g. it checks norminv, normcdf, normpdf, sort, matrix division and multip...
nansum
NANSUM same as SUM but ignores NaN's.
nanstd
NANSTD same as STD but ignores NaN's.
nanconv
NANCONV computes the convolution for data with missing values.
nanfft
NANFFT calculates the Fourier-Transform of X for data with missing values.
nanfilter
NANFILTER is able to filter data with missing values encoded as NaN.
nanfilter1uc
NANFILTER1UC is an adaptive filter for data with missing values encoded as NaN.
normpdf
NORMPDF returns normal probability density
normcdf
NORMCDF returns normal cumulative distribtion function
norminv
NORMINV returns inverse cumulative function of the normal distribution
meandev
MEANDEV estimates the Mean deviation (note that according to [1,2] this is the mean deviation; not the mean absolute deviation)
percentile
PERCENTILE calculates the percentiles of histograms and sample arrays.
quantile
QUANTILE calculates the quantiles of histograms and sample arrays.
rankcorr
RANKCORR calculated the rank correlation coefficient.
ranks
RANKS gives the rank of each element in a vector.
rms
RMS calculates the root mean square can deal with complex data.
sumskipnan
SUMSKIPNAN adds all non-NaN values.
var
VAR calculates the variance.
mean
MEAN calculates the mean of data elements.
sem
SEM calculates the standard error of the mean [SE,M] = SEM(x [, DIM [,W]]) calculates the standard error (SE) in dimension DIM the default DIM is the first non-single dimension M retur...
spearman
SPEARMAN Spearman's rank correlation coefficient.
trimean
TRIMEAN yields the weighted mean of the median and the quartiles m = TRIMEAN(y).
tpdf
TPDF returns student probability density
tcdf
TCDF returns student cumulative distribtion function
tinv
TINV returns inverse cumulative function of the student distribution
zscore
ZSCORE removes the mean and normalizes data to a variance of 1.
flag_implicit_significance
The use of FLAG_IMPLICIT_SIGNIFICANCE is in experimental state.
xcovf
XCOVF generates cross-covariance function.
train_sc
Train a (statistical) classifier CC = train_sc(D,classlabel) CC = train_sc(D,classlabel,MODE) CC = train_sc(D,classlabel,MODE, W) weighting D(k,:) with weight W(k) (not all classifiers su...
test_sc
TEST_SC: apply statistical and SVM classifier to test data
xval
XVAL is used for crossvalidation
classify
CLASSIFY classifies sample data into categories defined by the training data and its group information
train_lda_sparse
Linear Discriminant Analysis for the Small Sample Size Problem as described in Algorithm 1 of J.
decovm
decompose extended covariance matrix into mean (mu), standard deviation, the (pure) Covariance (COV), correlation (xc) matrix and the correlation coefficients R2.
gscatter
GSCATTER scatter plot of groups
mahal
MAHAL return the Mahalanobis' D-square distance between the multivariate samples x and y, which must have the same number of components (columns), but may have a different number of observatio...
cdfplot
CDFPLOT plots empirical commulative distribution function
hist2res
Evaluates Histogram data [R]=hist2res(H)
fss
FSS - feature subset selection and feature ranking the method is motivated by the max-relevance-min-redundancy (mRMR) approach [1].
cat2bin
CAT2BIN converts categorical into binary data each category of each column in D is converted into a logical column B = cat2bin(C); [B,BinLabel] = cat2bin(C,Label); [B,BinLabel] = ...
ttest
TTEST (paired) t-test For a sample X from a normal distribution with unknown mean and variance, perform a t-test of the null hypothesis `mean (X) == M'.
ttest2
TTEST2 (unpaired) t-test For two samples x and y from normal distributions with unknown means and unknown equal variances, perform a two-sample t-test of the null hypothesis of equa...
xptopen
Not documented
bland_altman
BLAND_ALTMANN shows the Bland-Altman plot of two columns of measurements and computes several summary results.
cumsumskipnan
CUMSUMSKIPNAN Cumulative sum while skiping NaN's.
range
RANGE calculates the range of Y Missing values (encoded as NaN) are ignored.
signrank
SIGNRANK - Wilcoxon signed-rank test The Wilcoxon signed-rank test is a non-parametric statistical hypothesis test used to compare two related samples whether their population median ...
histo
HISTO calculates histogram for each column [H,X] = HISTO(Y,Mode) Mode 'rows' : frequency of each row '1x' : single bin-values 'nx' : separate bin-values for each column X are...
histo2
HISTO2 calculates histogram for multiple columns with separate bin values for each data column.
histo3
HISTO3 calculates histogram for multiple columns with common bin values among all data columns, and can be useful for data compression.
histo4
HISTO4 calculates histogram of multidimensional data samples and supports data compression
kolmogorov_smirnov
KOLMOGOROV_SMIRNOV computes the two-sample Kolmogorov-Smirnov test for each pair columns.
kstest2
KSTEST2 computes the two-sampleKolmogorov-Smirnov.
roc
ROC plots receiver operator curve and computes derived statistics. computes the ROC curve, and a number of derived paramaters include AUC, optimal threshold values, corresponding confusion m...
kappa
KAPPA estimates Cohen's kappa coefficient and related statistics
load_cifar100
LOAD_CIFAR100 loads cifar100 data [1,2].
load_cifar10
LOAD_CIFAR10 loads cifar10 data [1,2].
load_mnist
LOAD_MNIST load MNIST database [1] Usage: [train_data, train_labels, test_data, test_labels] = load_mnist(); References: [1] Yann LeCun, Corinna Cortes, Christopher J.C.
fishers_exact_test
FISHERS_EXACT_TEST implements Fisher's exact test for the analysis of contincency tables e.g. "Lady tasting tea" experiment [1-6].
betapdf
pdf = betapdf (x, a, b) For each element of x, compute the probability density function (PDF) at x of the Beta distribution with parameters a and b.
betacdf
cdf = betacdf (x, a, b) For each element of @var{x}, compute the cumulative distribution function (CDF) at x of the Beta distribution with parameters a and b.
betainv
inv = betainv (x, a, b) For each element of x, compute the quantile (the inverse of the CDF) at x of the Beta distribution with parameters a and b.
gini
GINI computes the gini-coefficient [1] using by computing the L-moments [2].
lmom
LMOM estimates the L-Moments [1,2] from a sample distribution and might be a useful density estimation [1,3].
corrplot
CORRPLOT displays the correlation plot
knnsearch
KNNSEARCH search for K nearest neighbors and related statistics

Package: nan