v1.8.1

• Use \doi{} markup in Rd files.
• New function gytb() to generate the Genotype by yield*trait biplot.
• New functions row_col_mean() and row_col_sum()to add a row with the mean/sum of each variable and a column with the the mean/sum for each row of a matrix or data frame.
• New functions has_zero(), remove_cols_zero(), remove_rows_zero(), select_cols_zero(), select_rows_zero(), and replace_zero() to deal with 0s in a data frame.
• Fix bug of inconsistent color legend when plotting objects of class gge.
• Include class gge and can_corr in get_model_data().
• New argument position in plot.gamem() and plot.mtsi() to control the position adjustment of the bar plot.
• New argument col.by in corr_plot() to map the color of the points by a categorical variable.
• New argument use_data in functions mgidi(), fai_blup(), and Smith_Hazel() to control which data is used (BLUPs or phenotypic means) to compute the index.
• inspect() now generate a warning if zero values are observed in data.

v1.7.0

• New functions clip_read() and clip_write() to read from the clipboard and write to the clipboard, respectively.
• New function sum_by() to compute the sum by levels of factors.
• Update wsmp.R (#7). Thank you @BartoszKozak for your contribution.
• mgidi() now allows using a fixed-effect model fitted with gafem() as input data.
• round_cols() now can be used to round whole matrices.

v1.6.1

• plot.mgidi() can now plot the contribution for all genotypes.
• plot_bars() and plot_factbars() now shows the values with values = TRUE
• Update the functions by using the new dplyr::across()
• Update citation field by including number and version of the published paper.

v1.6.0

New functions

• Smith_Hazel() and print.sh() and plot.sh() for computing the Smith and Hazel selection index.
• coincidence_index() for computing the coincidence index.

Minor improvements

• get_model_data() now extracts the genotypic and phenotypic variance-covariance matrix from objects of class gamem and waasb.
• fai_blup() now returns the total genetic gain and the list with the ideotypes' construction.
• mgidi() now computes the genetic gain when a mixed-model is used as input data.
• The S3 method plot() for objects of class mgidi has a new argument type = "contribution" to plot the contribution of each factor in the MGIDI index.
• plot_scores() now can produce a biplot showing other axes besides PC1 and PC2. To change the default IPCA in each axis use the new arguments first and second.

v1.5.0

New functions

• select_rows_na() and select_cols_na() to select rows or columns with with NA values.
• mgidi() to compute the multi-trait genotype-ideotype distance index.
• plot_bars() to create bar plots quickly. Thanks to @MariaDiel for her suggestion.

Minor changes

• Deprecated functions hm_mean() and gm_mean() removed in favour of hmean() and gmean(), respectively.
• Deprecated argument rep retired in Fox(), ge_effects(), Huehn(), resp_surf(), superiority(), and Thennarasu()
• Deprecated argument verbose retired in anova_ind()
• Deprecated argument region retired in resp_surf()
• Remove dependency on dendextend by using ggplot2-based graphics in plot.wsmp().
• Update package site with pkgdown v1.5.0.
• Update documentation in ge_plot()
• Allow using fai_blup() with gamem()
• Improve checking process with inspect()
• Improve feedback for results, indicating random and fixed effects. Thanks to @NelsonJunior for his suggestion.
• plot() call on objects of class gamem, waasb and waas now returns the variable names automatically. Thanks to @MdFarhad for suggesting me this change.
• plot.gamem() and plot.waasb() have a new argument (type = "vcomp") to produce a plot showing the contribution of the variance components to the phenotypic variance
• cv_ammi(), cv_ammif(), and cv_blup() now check for missing values and unbalanced data before computing the cross-validation. (#3)

Bug fixes

• Fix problems from a recent upgrade of package tibble to version 3.0.0.
• get_model_data() now fills rows that don't matches across columns with NA. Thanks to @MdFarhad for his report.
• get_model_data() called now report mean squares, F-calculated and P-values for blocks within replicates in anova_ind().

v1.4.0

Bug fixes

• Factor columns can now have custom names rather than ENV, GEN, and REP only (#2).

New functions

• gmd() a shortcut to get_model_data()
• gtb() to generate a genotype-by-trait biplot.
• gamem_met() to analyze genotypes in multi-environment trials using mixed- or random-effect models allowing unbalanced data. Thanks to @EderOliveira for his e-mail.
• has_class() to check if a class exists.
• impute_missing_val() to impute missing values in a two-way table based on Expectation-Maximization algoritms.
• non_collinear_vars() to select a set of predictors with minimal multicollinearity.
• replace_na() to replace NA values quicly.
• random_na() to generate random NA values based on a desired proportion.

Minor changes

• gge(), performs_ammi(), waas(), and waasb() now handle with unbalanced data by implementing a low-rank matrix approximation using singular value decomposition to impute missing entires. Imputation generates a warning message.
• NA values are checked and removed with a warning when computing stability indexes. Thanks to @MdFarhad for alerting me.
• New argument plot_res in path_coeff() to create a residual plot of the multiple regression model.
• Update the citation file to include the published official reference.
• Argument verbose deprecated in functions anova_ind() and split_factors()
• Argument rep deprecated in functions Fox(), Huehn(), superiority(), and Thennarasu().
• Deprecated argument means_by removed in functions can_corr() and clustering().
• Deprecated argument verbose removed in functions colindiag() and split_factors().
• Deprecated argument values removed in functions desc_stat() and find_outliers().
• Deprecated argument var removed in function desc_wider().
• Remove dependency on lattice by using ggplot2 in plot.resp_surf().
• An up-to-date cheat sheet was included.

v1.3.0

New functions

• alpha_color() To get a semi-transparent color
• gafem() To analyze genotypes using fixed-effect models.
• residual_plots() A helper function to create residuals plots.
• stars_pval() To generate significance stars from p-values
• doo() An alternative to dplyr::do for doing anything

utils_stats

• cv_by() For computing coefficient of variation by levels of a factor.
• max_by() For computing maximum values by levels of a factor.
• means_by() For computing arithmetic means by levels of a factor.
• min_by() For computing minimum values by levels of a factor.
• n_by() For getting the length.
• sd_by() For computing sample standard deviation.
• sem_by() For computing standard error of the mean by levels of a factor.
• av_dev() computes the average absolute deviation.
• ci_mean() computes the confidence interval for the mean.
• cv() computes the coefficient of variation.
• hm_mean(), gm_mean() computes the harmonic and geometric means, respectively. The harmonic mean is the reciprocal of the arithmetic mean of the reciprocals. The geometric mean is the nth root of n products.
• kurt() computes the kurtosis like used in SAS and SPSS.
• range_data() Computes the range of the values.
• sd_amo(), sd_pop() Computes sample and populational standard deviation, respectively.
• sem() computes the standard error of the mean.
• skew() computes the skewness like used in SAS and SPSS.
• sum_dev() computes the sum of the absolute deviations.
• sum_sq_dev() computes the sum of the squared deviations.
• var_amo(), var_pop() computes sample and populational variance.
• valid_n() Return the valid (not NA) length of a data.

utils_rows_cols

• colnames_to_lower(), colnames_to_upper(), and colnames_to_title() to translate column names to lower, upper and title cases quickly.

utils_num_str

• all_lower_case(), all_upper_case(), and all_title_case() to translate strings vectors or character columns of a data frame to lower, upper and title cases, respectively.
• tidy_strings() Tidy up characters strings, non-numeric columns, or any selected columns in a data frame by putting all word in upper case, replacing any space, tabulation, punctuation characters by '_', and putting '_' between lower and upper cases.
• find_text_in_num() Find text fragments in columns assumed to be numeric. This is especially useful when everything() is used in argument resp to select the response variables.

New arguments

• anova_ind(), anova_joint(), performs_ammi(), waas() and waasb(), now have the argument block to analyze data from trials conducted in an alpha-lattice design. Thanks to @myaseen208 for his suggestion regarding multi-environment trial analysis with alpha-lattice designs.
• argument repel included in plot_scores() to control wheater the labels are repelled or not to avoid overlapping.

Deprecated arguments

Argument means_by was deprecated in functions can_corr() and clustering(). Use means_by() to pass data based on means of factor to these functions.

Minor changes

• Change "#000000FF" with "#FFFFFF00" in transparent_color()
• desc_stat() now handles grouped data passed from dplyr::group_by()
• plot_scores() now support objects of class waas_mean.
• Include inst/CITATION to return a reference paper with citation("metan").
• Change 'PC2' with 'PC1' in y-axis of plot_scores(type = 2) (#1)
• get_model_data() now support models of class anova_joint and gafem and extract random effects of models fitted with waasb() and gamem().
• Update plot.waasb() and plot.gamem() to show distribution of random effects.
• inspect(), cv_blup(), cv_ammif(), and cv_ammi() now generate a warning message saying that is not possible to compute cross-validation procedures in experiments with two replicates only. Thanks to @Vlatko for his email.
• plot.wsmp() now returns heatmaps created with ggplot2. Thus, we removed dependency on gplots.
• Vignettes updated

First release on CRAN

The first release of the package CRAN

v1.1.0

I'm very pleased to announce the release of metan 1.1.0, This is a minor release with bug fixes and new functions. The most important changes are described below.

• New function corr_stab_ind() for computing Spearman's rank correlation between stability indexes;
• New function corr_coef() for computing correlation coefficients and p-values;
• New S3 method plot.corr_coef() for creating correlation heat maps;
• New S3 method print.corr_coef() for printing correlation and p-values;
• New helper functions make_lower_tri() and make_upper_tri() for creating lower and upper triangular matrices, respectively.
• New helper function reorder_cormat() for reordering a correlation matrix according to the correlation coefficients;
• Improve usability of get_model_data() by supporting new classes of models. Now, get_model_data() can be used to get all statistics or ranks computed with the wrapper function ge_stats().
• arrange_ggplot() now support objects of class ggmatrix.
• Change the default plot theme to theme_metan()
• Update function's documentation;
• Update vignettes.

v1.0.1

• New function gamem() for analyzing genotypes in one-way trials using mixed-effect models;
• New function desc_wider() to convert an output of the function desc_stat() to a 'wide' format;
• New function Fox() for Stability analysis;
• New function Shukla() for stability analysis;
• New function to_factor() to quickly convert variables to factors;
• Improve usability of get_model_data() function;
• Update function's doccumentation;
• Update vignettes;