The symbols used in the help pages and vignettes of DiallelAnalysisR, with their meaning and the argument or result component that holds them. The notation follows one rule throughout: scalars are upper-case letters in normal face (\(P\), \(R\)), indices lower-case italic (\(i, j\)), vectors lower-case bold (\(\mathbf{y}\), \(\boldsymbol{\beta}\)) and matrices upper-case bold (\(\mathbf{X}\), \(\boldsymbol{\Sigma}\)).
Usage
da_notation(format = c("table", "path", "tex"))See also
Other DiallelAnalysisR utilities:
da_export(),
da_reference(),
da_save(),
da_theme()
Author
Muhammad Yaseen (myaseen208@gmail.com)
Examples
da_notation(
format = c("table", "path", "tex")[1]
)
#> symbol text
#> <char> <char>
#> 1: P P
#> 2: B B
#> 3: i, j, k, l i j k l
#> 4: \\mathbf{Y} Y
#> 5: Y_{ij} Y_ij
#> 6: Y_{i\\cdot}, Y_{\\cdot j}, Y_{\\cdot\\cdot} Y_i. Y_.j Y_..
#> 7: \\mathbf{T} T
#> 8: \\mu mu
#> 9: \\mathbf{g}, g_i g g_i
#> 10: \\mathbf{S}, S_{ij} S S_ij
#> 11: \\mathbf{R}, R_{ij} R R_ij
#> 12: MS_E, f_E MS_E f_E
#> 13: \\sigma^2_m sigma^2_m
#> 14: SS_g, SS_s, SS_r SS_g SS_s SS_r
#> 15: \\sigma^2_g, \\sigma^2_s, \\sigma^2_r sigma^2_g sigma^2_s sigma^2_r
#> 16: \\sigma^2_A, \\sigma^2_D sigma^2_A sigma^2_D
#> 17: V_r, W_r Vr Wr
#> 18: V_{0L0}, V_{1L1}, V_{0L1}, W_{0L01} V0L0 V1L1 V0L1 W0L01
#> 19: D, H_1, H_2, F, h^2, E D H1 H2 F h2 E
#> 20: L, M L M
#> 21: \\mathbf{g}^{I}, \\mathbf{g}^{II} gI gII
#> symbol text
#> <char> <char>
#> kind
#> <char>
#> 1: scalar
#> 2: scalar
#> 3: index
#> 4: matrix
#> 5: element
#> 6: scalar
#> 7: matrix
#> 8: scalar
#> 9: vector
#> 10: matrix
#> 11: matrix
#> 12: scalar
#> 13: scalar
#> 14: scalar
#> 15: scalar
#> 16: scalar
#> 17: scalar
#> 18: scalar
#> 19: scalar
#> 20: scalar
#> 21: vector
#> kind
#> <char>
#> meaning
#> <char>
#> 1: number of parents
#> 2: number of replicates (blocks)
#> 3: parents; i female (Cross1), j male (Cross2)
#> 4: P x P matrix of cell means (female parents in rows)
#> 5: mean of cross i x j
#> 6: row, column and grand totals of the cell means
#> 7: cell totals over replicates (Hayman)
#> 8: general mean
#> 9: general combining ability (gca) effects
#> 10: specific combining ability (sca) effects, symmetric
#> 11: reciprocal effects, R_ij = -R_ji
#> 12: error mean square of the block analysis and its degrees of freedom
#> 13: error variance of a cell mean, MS_E / B
#> 14: sums of squares of gca, sca and reciprocal effects
#> 15: variances of gca, sca and reciprocal effects (random model)
#> 16: additive and dominance variances
#> 17: variance of array r and its covariance with the parents (Hayman)
#> 18: variance of the parents, mean of Vr, variance of array means, mean of Wr
#> 19: Hayman's components of variation
#> 20: numbers of parents in the two groups of a partial diallel
#> 21: gca effects of the two groups (partial diallel)
#> meaning
#> <char>
#> argument
#> <char>
#> 1:
#> 2:
#> 3: Cross1, Cross2
#> 4: Means
#> 5: Means
#> 6:
#> 7:
#> 8:
#> 9: GCA
#> 10: SCA
#> 11: Reciprocal
#> 12: RCBD
#> 13: ANOVA (line Error)
#> 14: ANOVA
#> 15: Genetic.Components
#> 16: Genetic.Components
#> 17: Wr.Vr.Table
#> 18: VOLO
#> 19: Components.of.Variation
#> 20:
#> 21: General
#> argument
#> <char>