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Package {NeutroCrdRcbdAnalysis}

Type: Package
Title: Neutrosophic Analysis of Completely Randomized Designs and Randomized Complete Block Designs
Version: 0.0.1
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Provides neutrosophic analysis of variance (NANOVA) and analysis of covariance (NANCOVA) for Completely Randomized Designs (CRD) and Randomized Complete Block Designs (RCBD) using interval-valued observations. Computes interval sums of squares, mean squares, F-statistics, significance tests, and interval-based least significant difference (LSD) comparisons. When lower and upper observations are identical (crisp data), the methods reduce to the corresponding classical ANOVA and ANCOVA.
License: GPL-3
Encoding: UTF-8
Imports: MASS, stats
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-07-14 11:08:38 UTC; admin
Author: Neethu R.S. [aut, ctb], Boyina Devi Priyanka [aut, ctb], Cini Varghese [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb], Vinaykumar L.N. [aut, cre]
Repository: CRAN
Date/Publication: 2026-07-22 08:30:26 UTC

Neutrosophic Analysis of Covariance for Completely Randomized Design

Description

Performs Neutrosophic Analysis of Covariance (NANCOVA) for interval-valued response and covariate data from a Completely Randomized Design (CRD).

Usage

CRDnsANCOVA(
  Lower_y,
  Upper_y,
  Lower_z,
  Upper_z,
  design,
  alpha = 0.05,
  verbose = FALSE
)

Arguments

Lower_y

Numeric matrix of lower bounds of the response variable.

Upper_y

Numeric matrix of upper bounds of the response variable.

Lower_z

Numeric matrix of lower bounds of the covariate.

Upper_z

Numeric matrix of upper bounds of the covariate.

design

Numeric matrix representing the CRD treatment layout.

alpha

Significance level for interval-based LSD comparisons. Default is 0.05.

verbose

Logical. If TRUE, prints the NANCOVA table and LSD comparisons.

Value

A list containing the Neutrosophic ANCOVA table, interval LSD comparisons (if treatment effects are significant), and the interval LSD value.

Examples

Lower_y <- matrix(c(
  20,25,30,35,
  21,26,31,36,
  19,24,29,34,
  20,25,30,35,
  21,26,31,36
), nrow = 5, byrow = TRUE)

Upper_y <- matrix(c(
  22,27,32,37,
  23,28,33,38,
  21,26,31,36,
  22,27,32,37,
  23,28,33,38
), nrow = 5, byrow = TRUE)

Lower_z <- matrix(c(
  8,9,10,11,
  9,10,11,12,
  8,9,10,11,
  9,10,11,12,
  8,9,10,11
), nrow = 5, byrow = TRUE)

Upper_z <- matrix(c(
  9,10,11,12,
  10,11,12,13,
  9,10,11,12,
  10,11,12,13,
  9,10,11,12
), nrow = 5, byrow = TRUE)

design <- matrix(c(
  1,2,3,4,
  1,2,3,4,
  1,2,3,4,
  1,2,3,4,
  1,2,3,4
), nrow = 5, byrow = TRUE)

CRDnsANCOVA(Lower_y, Upper_y, Lower_z, Upper_z, design)

Neutrosophic Analysis of Variance for Completely Randomized Design

Description

Performs neutrosophic analysis of variance (NANOVA) for a completely randomized design using interval-valued observations.

Usage

CRDnsANOVA(Lower_y, Upper_y, design, alpha = 0.05, verbose = FALSE)

Arguments

Lower_y

Matrix of lower bounds of the response variable.

Upper_y

Matrix of upper bounds of the response variable.

design

Matrix specifying treatment allocation.

alpha

Significance level for LSD test.

verbose

Logical. If TRUE, prints the analysis.

Value

A list containing the NANOVA table, treatment means, pairwise comparisons, and LSD interval.

Examples

Lower_y <- matrix(c(
  9.5, 19.5, 29.5, 39.5,
  10.0, 20.0, 30.0, 40.0,
  10.5, 20.5, 30.5, 40.5,
  9.8, 19.8, 29.8, 39.8,
  10.2, 20.2, 30.2, 40.2
), nrow = 5, byrow = TRUE)

Upper_y <- matrix(c(
  10.5, 20.5, 30.5, 40.5,
  11.0, 21.0, 31.0, 41.0,
  11.5, 21.5, 31.5, 41.5,
  10.8, 20.8, 30.8, 40.8,
  11.2, 21.2, 31.2, 41.2
), nrow = 5, byrow = TRUE)

design <- matrix(c(
  1, 2, 3, 4,
  1, 2, 3, 4,
  1, 2, 3, 4,
  1, 2, 3, 4,
  1, 2, 3, 4
), nrow = 5, byrow = TRUE)

CRDnsANOVA(
  Lower_y = Lower_y,
  Upper_y = Upper_y,
  design = design,
  alpha = 0.05,
  verbose = TRUE
)

Neutrosophic Analysis of Covariance for RCBD

Description

Performs neutrosophic analysis of covariance for a Randomized Complete Block Design using interval-valued response and covariate data.

Usage

RCBDnsANCOVA(
  Lower_y,
  Upper_y,
  Lower_z,
  Upper_z,
  design,
  alpha = 0.05,
  verbose = FALSE
)

Arguments

Lower_y

Numeric matrix of lower response values.

Upper_y

Numeric matrix of upper response values.

Lower_z

Numeric matrix of lower covariate values.

Upper_z

Numeric matrix of upper covariate values.

design

Numeric matrix representing the RCBD layout.

alpha

Significance level for LSD test. Default is 0.05.

verbose

Logical; if TRUE, prints the analysis. Default is FALSE.

Value

A list containing the NANCOVA table, LSD interval, and treatment comparisons (if treatment effect is significant).

Examples

Lower_y <- matrix(c(
  46.84, 97.69, 39.30, 49.20,
  51.52, 83.38, 56.48, 42.15,
  44.42, 49.64, 44.21, 35.79,
  32.77, 74.30, 55.72, 70.55
), nrow = 4, byrow = TRUE)

Upper_y <- matrix(c(
  49.66,101.31,47.70,55.80,
  60.98,87.62,60.52,44.85,
  52.26,59.36,52.79,44.61,
  42.23,82.70,59.28,75.45
), nrow = 4, byrow = TRUE)

Lower_z <- matrix(c(
  224.95,245.87,245.19,259.41,
  222.06,213.83,253.10,247.51,
  255.67,230.55,265.05,246.67,
  137.98,214.68,251.49,257.70
), nrow = 4, byrow = TRUE)

Upper_z <- matrix(c(
  229.05,250.13,252.81,268.59,
  229.94,222.17,258.90,256.49,
  262.33,237.45,274.95,249.33,
  142.02,219.32,260.51,264.30
), nrow = 4, byrow = TRUE)

design <- matrix(c(
  1,2,3,4,
  1,2,3,4,
  1,2,3,4,
  1,2,3,4
), nrow = 4, byrow = TRUE)

result <- RCBDnsANCOVA(
  Lower_y,
  Upper_y,
  Lower_z,
  Upper_z,
  design,
  alpha = 0.05,
  verbose = TRUE
)

Neutrosophic Analysis of Variance for Randomized Complete Block Design

Description

Performs Neutrosophic Analysis of Variance (NANOVA) for interval-valued response data from a Randomized Complete Block Design (RCBD).

Usage

RCBDnsANOVA(Lower_y, Upper_y, design, alpha = 0.05, verbose = FALSE)

Arguments

Lower_y

Numeric matrix of lower bounds of the response variable.

Upper_y

Numeric matrix of upper bounds of the response variable.

design

Numeric matrix representing the RCBD layout.

alpha

Significance level for interval-based LSD test. Default is 0.05.

verbose

Logical. If TRUE, prints the NANOVA table and LSD comparisons.

Value

A list containing the Neutrosophic ANOVA table, interval-based LSD comparisons (if applicable), and the interval LSD.

Examples

Lower_y <- matrix(c(
  120.230,125.488,132.987,127.086,127.672,128.013,
  122.594,121.009,123.969,120.358,120.424,122.197,
  121.183,130.671,128.794,114.863,122.595,122.073,
  127.620,124.532,132.893,125.528,125.850,127.550
), nrow = 4, byrow = TRUE)

Upper_y <- matrix(c(
  127.6967536,131.2116955,141.2127373,136.1540904,130.6884772,136.8474149,
  129.8264289,130.3314544,133.3113414,126.5063118,128.4362999,130.2714433,
  124.5068016,139.3287297,134.1060197,124.2774447,127.2248520,130.3948469,
  131.0638721,129.8884785,135.5666716,127.7580663,132.0178679,133.3903886
), nrow = 4, byrow = TRUE)

design <- matrix(c(
  1,2,3,4,5,6,
  1,2,3,4,5,6,
  1,2,3,4,5,6,
  1,2,3,4,5,6
), nrow = 4, byrow = TRUE)

RCBDnsANOVA(Lower_y, Upper_y, design)

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They may not be fully stable and should be used with caution. We make no claims about them.
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