Computes (i) within-environment analysis of variance, GEI effect, GEI means, and genotype plus GEI effects; (ii) parametric statistics including AMMI-based indexes, Annicchiarico's genotypic confidence index (1992), Ecovalence (Wricke, 1965), regression-based stability (Eberhart and Russell., 1966), Shukla's stability variance parameter (1972); and (iii) nonparametric statistics including Fox's stability function (Fox et al. 1990), superiority index (Lin and Binns, 1988), Huehn's stability statistics (Huehn, 1979), and Thennarasu (1995) statistics.
ge_stats(.data, env, gen, rep, resp, verbose = TRUE, prob = 0.05)The dataset containing the columns related to Environments, Genotypes, replication/block and response variable(s).
The name of the column that contains the levels of the environments.
The name of the column that contains the levels of the genotypes.
The name of the column that contains the levels of the replications/blocks.
The response variable(s). To analyze multiple variables in a
single procedure use, for example, resp = c(var1, var2, var3).
Logical argument. If verbose = FALSE the code will run
silently.
The probability error assumed.
An object of class ge_stats which is a list with one data
frame for each variable containing the computed indexes.
The function computes the statistics and ranks for the following
stability indexes. "Y" (Response variable), "CV" (coefficient
of variation), "Var" (Genotype's variance), "Shukla"
(Shukla's variance, calling Shukla internally), "Wi_g",
"Wi_f", "Wi_u" (Annichiarrico's genotypic confidence index for all,
favorable and unfavorable environments, respectively, calling
Annicchiarico internally ), "Ecoval" (Wricke's
ecovalence, ecovalence internally), "Sij" (Deviations
from the joint-regression analysis) and "R2" (R-squared from the
joint-regression analysis, calling ge_reg internally),
"ASV" (AMMI-stability value), "SIPC" (sum of the absolute
values of the IPCA scores), "EV" (Average of the squared eigenvector
values), "ZA" (Absolute values of the relative contributions of the
IPCAs to the interaction), and "WAAS" (Weighted Average of Absolute
Scores), by calling AMMI_indexes internally; "HMGV"
(Harmonic mean of the genotypic value), "RPGV" (Relative performance
of the genotypic values), "HMRPGV" (Harmonic mean of the relative
performance of the genotypic values), by calling
Resende_indexes internally; "Pi_a", "Pi_f", "Pi_u"
(Superiority indexes for all, favorable and unfavorable environments,
respectively, calling superiority internally), "Gai"
(Geometric adaptability index, calling gai internally),
"S1" (mean of the absolute rank differences of a genotype over the n
environments), "S2" (variance among the ranks over the k
environments), "S3" (sum of the absolute deviations), "S6"
(relative sum of squares of rank for each genotype), by calling
Huehn internally; and "N1", "N2", "N3", "N4"
(Thennarasu"s statistics, calling Thennarasu internally ).
Annicchiarico, P. 1992. Cultivar adaptation and recommendation from alfalfa trials in Northern Italy. Journal of Genetic \& Breeding, 46:269-278
Eberhart, S.A., and W.A. Russell. 1966. Stability parameters for comparing Varieties. Crop Sci. 6:36-40. doi:10.2135/cropsci1966.0011183X000600010011x
Fox, P.N., B. Skovmand, B.K. Thompson, H.J. Braun, and R. Cormier. 1990. Yield and adaptation of hexaploid spring triticale. Euphytica 47:57-64. doi:10.1007/BF00040364.
Huehn, V.M. 1979. Beitrage zur erfassung der phanotypischen stabilitat. EDV Med. Biol. 10:112.
Kang, M.S., and H.N. Pham. 1991. Simultaneous Selection for High Yielding and Stable Crop Genotypes. Agron. J. 83:161. doi:10.2134/agronj1991.00021962008300010037x.
Lin, C.S., and M.R. Binns. 1988. A superiority measure of cultivar performance for cultivar x location data. Can. J. Plant Sci. 68:193-198. doi:10.4141/cjps88-018
Olivoto, T., A.D.C. L\'ucio, J.A.G. da silva, V.S. Marchioro, V.Q. de Souza, and E. Jost. 2019a. Mean performance and stability in multi-environment trials I: Combining features of AMMI and BLUP techniques. Agron. J. 111:2949-2960. doi:10.2134/agronj2019.03.0220
Shahbazi, E. 2019. Genotype selection and stability analysis for seed yield of Nigella sativa using parametric and non-parametric statistics. Sci. Hortic. (Amsterdam). 253:172-179. doi:10.1016/j.scienta.2019.04.047.
Shukla, G.K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity. 29:238-245. doi:10.1038/hdy.1972.87.
Thennarasu, K. 1995. On certain nonparametric procedures for studying genotype x environment interactions and yield stability. Ph.D. thesis. P.J. School, IARI, New Delhi, India.
Wricke, G. 1965. Zur berechnung der okovalenz bei sommerweizen und hafer. Z. Pflanzenzuchtg 52:127-138.
# NOT RUN {
library(metan)
model <- ge_stats(data_ge, ENV, GEN, REP, GY)
get_model_data(model, "stats")
# }
# NOT RUN {
# }
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