Provides neutrosophic extensions of Lahiri's method to select a random sample
     of size n using probability proportional to size without replacement (PPSWOR) sampling. It computes
     the corresponding neutrosophic inclusion probabilities and provides estimates of the population total
    and mean using both the neutrosophic Horvitz Thompson (NHT) estimator
    and the neutrosophic generalized regression (NGREG) estimator and its percent relative efficiency.

Description: Provides methods for Neutrosophic Analysis of Variance (NANOVA) 
    and Neutrosophic Analysis of Covariance (NANCOVA) for row-column designs, 
    including Latin square designs and Youden square designs, using 
    interval-valued observations. The package computes neutrosophic sums of 
    squares, mean squares, interval-valued F-statistics, significance tests, 
    and multiple comparisons using Least Significant Difference (LSD) 
    procedures. For crisp data, users may enter identical lower and upper 
    values of responses to obtain classical Analysis of Variance (ANOVA) 
    results. Similarly, users may enter identical lower and upper values for 
    both responses and covariates to obtain classical Analysis of Covariance 
    (ANCOVA) results.

Provides methods for Neutrosophic Analysis of Variance
    (NANOVA) for split-plot and strip-plot experimental designs using
    interval-valued observations. The package computes neutrosophic sums
    of squares, mean squares, interval-valued F-statistics, significance
    tests, and Least Significant Difference (LSD) based multiple
    comparisons for main plot, sub plot, horizontal factor, vertical
    factor, and interaction effects. For crisp data, users may provide
    identical lower and upper response values to obtain results equivalent
    to classical analysis of variance. The basic idea of neutrosophic
    statistics is obtained from Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, 
    while the analysis procedures implemented in this package are newly developed.