Statistics
avg | Computes the average of a variable regardless of dimensionality. |
betainc | Evaluates the incomplete beta function. |
bin_avg | Calculates gridded binned averages and counts on a rectilinear grid using randomly spaced data. |
bin_sum | Calculates binned sums and counts over multiple invocations of the procedure on a rectilinear grid. |
bootstrap_correl | Bootstrap estimates of sample cross correlations (ie, Pearson's correlation coefficient) between two variables. |
bootstrap_diff | Bootstrap mean differences from two samples. |
bootstrap_estimate | Extract the user specified element from the bootstrapped values. |
bootstrap_regcoef | Bootstrap estimates of linear regression coefficient. |
bootstrap_stat | Bootstrap estimates of a user specified statistic derived from a variable. |
ceemdan | Complete Ensemble Empirical Mode Decomposition with Adaptive Noise. |
cohsq_c2p | Given coherence-squared and the effective degrees-of-freedom, calculate the associated probability. |
cohsq_p2c | Calculate the value(s) of coherence-squared required for a specified significance level and effectiove degrees-of-freedom. |
dim_acumrun_n | Calculates individual accumulated sums of sequences ('runs') of a specified length. |
dim_avg | Computes the average of a variable's rightmost dimension at all other dimensions. |
dim_avg_n | Computes the average of a variable's given dimension(s) at all other dimensions. |
dim_avg_n_Wrap | Computes the average of a variable's given dimensions at all other dimensions and retains metadata. |
dim_avg_wgt | Computes the weighted average of a variable's rightmost dimension at all other dimensions. |
dim_avg_wgt_n | Computes the weighted average of a variable's given dimension at all other dimensions. |
dim_avg_wgt_n_Wrap | Computes the weighted average of a variable's given dimension at all other dimensions and retains metadata. |
dim_avg_wgt_Wrap | Computes the weighted average of a variable's rightmost dimension at all other dimensions and retains metadata. |
dim_avg_Wrap | Computes the average of a variable's rightmost dimension at all other dimensions and retains metadata. |
dim_cumsum | Calculates the cumulative sum along the rightmost dimension. |
dim_cumsum_n | Calculates the cumulative sum along the given dimension(s). |
dim_cumsum_n_Wrap | Calculates the cumulative sum along the given dimension(s) and retains metadata. |
dim_cumsum_Wrap | Calculates the cumulative sum along the rightmost dimension and retains metadata. |
dim_gamfit_n | Fit data to the two parameter gamma distribution. |
dim_max | Finds the maximum of a variable's rightmost dimension at all other dimensions. |
dim_max_n | Finds the maximum of a variable's given dimensions at all other dimensions. |
dim_max_n_Wrap | Computes the maximum of a variable's given dimensions at all other dimensions and retains metadata. |
dim_median | Computes the median of a variable's rightmost dimension at all other dimensions. |
dim_median_n | Computes the median of a variable's given dimensions at all other dimensions. |
dim_min | Finds the minimum of a variable's rightmost dimension at all other dimensions. |
dim_min_n | Finds the minimum of a variable's given dimensions at all other dimensions. |
dim_min_n_Wrap | Computes the minimum of a variable's given dimensions at all other dimensions and retains metadata. |
dim_numrun_n | Counts the number of "runs" (sequences) within a series containing zeros and ones. |
dim_rmsd | Computes the root-mean-square-difference between two variables' rightmost dimension at all other dimensions. |
dim_rmsd_n | Computes the root-mean-square-difference between two variables' given dimensions at all other dimensions. |
dim_rmsd_n_Wrap | Computes the root-mean-square-difference between two variables' given dimensions at all other dimensions. |
dim_rmsd_Wrap | Computes the root-mean-square-difference between two variables' rightmost dimension at all other dimensions. |
dim_rmvmean | Calculates and removes the mean of the (rightmost) dimension at all other dimensions. |
dim_rmvmean_n | Calculates and removes the mean of the given dimension(s) at all other dimensions. |
dim_rmvmean_n_Wrap | Calculates and removes the mean of the given dimensions at all other dimensions and retains metadata. |
dim_rmvmean_Wrap | Calculates and removes the mean of the (rightmost) dimension at all other dimensions and retains metadata. |
dim_rmvmed | Calculates and removes the median of the (rightmost) dimension at all other dimensions. |
dim_rmvmed_n | Calculates and removes the median of the given dimension(s) at all other dimensions. |
dim_rmvmed_n_Wrap | Calculates and removes the median of the given dimensions at all other dimensions and retains metadata. |
dim_rmvmed_Wrap | Calculates and removes the median of the (rightmost) dimension at all other dimensions and retains metadata. |
dim_standardize | Calculates standardized anomalies of the rightmost dimension at all other dimensions. |
dim_standardize_n | Calculates standardized anomalies of the given dimension(s) at all other dimensions. |
dim_standardize_n_Wrap | Calculates standardized anomalies of the given dimensions at all other dimensions and retains metadata. |
dim_standardize_Wrap | Calculates standardized anomalies of the rightmost dimension at all other dimensions and retains metadata. |
dim_stat4 | Computes the first four moments (average, sample variance, skewness, and kurtosis) of the rightmost dimension for all other dimensions. |
dim_stat4_n | Computes the first four moments (average, sample variance, skewness, and kurtosis) of the given dimension(s) for all other dimensions. |
dim_stddev | Computes the sample standard deviation of a variable's rightmost dimension at all other dimensions. |
dim_stddev_n | Computes the sample standard deviation of a variable's given dimension(s) at all other dimensions. |
dim_stddev_n_Wrap | Computes the sample standard deviation of a variable's given dimension(s) at all other dimensions and retains metadata. |
dim_stddev_Wrap | Computes the sample standard deviation of a variable's rightmost dimension at all other dimensions and retains metadata. |
dim_sum_wgt_n_Wrap | Computes the weighted sum of a variable's given dimension at all other dimensions and retains metadata. |
dim_sum_wgt_Wrap | Computes the weighted sum of a variable's rightmost dimension at all other dimensions and retains metadata. |
dim_variance | Computes the unbiased estimates of the variance of a variable's rightmost dimension. |
dim_variance_n | Computes the unbiased estimates of the variance of a variable's given dimension(s) at all other dimensions. |
dim_variance_n_Wrap | Computes unbiased estimates of the variance of a variable's given dimension(s) at all other dimensions and retains metadata. |
dim_variance_Wrap | Computes unbiased estimates of the variance of a variable's rightmost dimension at all other dimensions and retains metadata. |
dtrend | Estimates and removes the least squares linear trend of the rightmost dimension from all grid points. |
dtrend_msg | Estimates and removes the least squares linear trend of the rightmost dimension from all grid points (missing values allowed). |
dtrend_msg_n | Estimates and removes the least squares linear trend of the dim-th dimension from all grid points (missing values allowed). |
dtrend_n | Estimates and removes the least squares linear trend of the given dimension from all grid points. |
dtrend_quadratic | Estimates and removes the least squares quadratic trend of the rightmost dimension from all grid points. |
dtrend_quadratic_msg_n | Estimates and removes the least squares quadratic trend of the dim-th dimension from all grid points (missing values allowed). |
eemd | Perform ensemble empirical mode decomposition (EEMD). |
equiv_sample_size | Estimates the number of independent values of a series of correlated observations. |
esccr | Computes sample cross-correlations. |
esccv | Computes sample cross-covariances. |
escorc | Computes the (Pearson) sample linear cross-correlations at lag 0 only. |
escorc_n | Computes the (Pearson) sample linear cross-correlations at lag 0 only, across the specified dimensions. |
escovc | Computes sample cross-covariances at lag 0 only. |
exponential_curve_fit | Calculates the coefficients for a simple exponential curve fit of the form ' y = A*exp(B*x)' using least squares. |
extval_frechet | Calculates the probability (PDF) and cumulative (CDF) distribution functions of the Frechet Type II distribution given the shape, scale and location parameters. |
extval_gev | Calculates the probability (PDF) and cumulative (CDF) distribution functions of the Generalized Extreme Value (GEV) distribution given the shape, scale and location parameters. |
extval_gumbel | Calculates the probability (PDF) and cumulative (CDF) distribution functions of the Gumbel (Type I) distribution function given the scale and location parameters. |
extval_mlegam | Estimates the location, shape, scale and other parameters for the Gamma distribution using maximum-likelihood estimation (MLE). |
extval_mlegev | Estimates the shape, scale and location parameters for the Generalized Extreme-Value (GEV) distribution using Maximum-Likelihood Estimation (MLE). |
extval_pareto | Calculates the probability (PDF) and cumulative (CDF) distribution functions of the Pareto distributions (Generalized, Type I, TYpe II) given the shape, scale and location parameters. |
extval_recurrence_table | Calculates the recurrence interval (return period), cumulative and exceedence probabilities based upon a time series. |
extval_return_period | Calculates the period of an event (eg, flood, heat wave, drought) occurring given an average event recurrence interval and specified probability level. |
extval_return_prob | Calculates the probability of an event (eg, flood, heat wave, drought) given an average event interval and a specified exceedance period. |
extval_weibull | Calculates the probability (PDF) and cumulative (CDF) distribution functions of the Weibull Type III distribution given the shape, scale and location parameters. |
ftest | Applies F-test for variances and returns an estimate of the statistical significance. |
genNormalDist | Generates a normal distribution. |
kde | Uses gaussian kernel density estimation (KDE) to estimate the probability density function of a random variable. This function is under construction and is available for testing only. It may not be released with NCL V6.5.0. |
kmeans_as136 | Performs k-means clustering via the Hartigan and Wong AS-136 algorithm. |
kolsm2_n | Uses the Kolmogorov-Smirnov two-sample test to determine if two samples are from the same distribution. |
max | Computes the maximum value of a multi-dimensional array. |
min | Computes the minimum value of a multi-dimensional array. |
pattern_cor | Compute centered or uncentered pattern correlation. |
pdfxy | Generates a joint probability density distribution. (Please use pdfxy_conform.) |
pdfxy_bin | Performs looping necessary to calculate the bivariate (joint) probability distribution (see pdfxy). |
pdfxy_conform | An interface to pdfxy that allows the input arrays to be different sizes. |
regcoef | Calculates the linear regression coefficient between two variables. |
regCoef | Calculates the linear regression coefficient between two variables. |
regCoef_n | Calculates the linear regression coefficient between two variables on the given dimensions. |
regline | Calculates the linear regression coefficient between two series. |
regline_weight | Calculates the linear regression coefficient between two series where the dependent (y) variable's values are weighted by some measure of uncertainty (typically, standard deviations) such that the Chi-square goodness-of-fit is minimized. |
spcorr | Computes Spearman rank order correlation (Rho) correlation coefficient. |
spcorr_n | Computes Spearman rank order correlation (Rho) correlation coefficient across the given dimension. |
stat2 | Calculates the first two moments of the given input. |
stat4 | Calculates estimates of the first four moments (mean, variance, skewness, and kurtosis) of the given input. |
stat_dispersion | Computes a number of robust statistics. |
stat_medrng | Calculates median, range, and mid-range of the given input. |
stat_trim | Calculates trimmed estimates of the first two moments of the given input. |
stddev | Calculates the sample standard deviation. |
student_t | Calculates the two-tailed probability of the Student-t distribution. |
taylor_stats | Calculates statistics needed for the Taylor Diagram: pattern_correlation, ratio and bias. |
trend_manken | Calculates Mann-Kendall non-parametric test for monotonic trend and the Theil-Sen robust estimate of linear trend. |
ttest | Returns an estimate of the statistical significance and, optionally, the t-values. |
variance | Computes an unbiased estimate the variance of all input points. |
weibull | Derives the shape and scale parameters for the Weibull distribution via maximum likelihood estimates. |