metan 1.4.0.9000 Unreleased

New functions

Minor changes

Bug fixes

metan 1.4.0 2020-03-17

Bug fixes

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

New functions

Minor changes

metan 1.3.0 2020-02-11

New functions

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

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

metan 1.2.1 2020-01-14

  • References describing the methods implemented in the package were included in description field of DESCRIPTION file as suggested by the CRAN team.

metan 1.2.0 Unreleased

metan 1.1.2 Unreleased

metan 1.1.1 Unreleased

  • Now on.exit() is used in S3 generic functions print() to ensure that the settings are reset when a function is excited.
  • Computationally intensive parts in vignettes uses pre-computed results.

metan 1.1.0 Unreleased

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.

metan 1.0.2 Unreleased

  • New function arrange_ggplot() for arranging ggplot2 graphics;
  • New function ge_effects() for computing genotype-environment effects;
  • New function gai() for computing the geometric adaptability index;
  • New helper function gm_mean() for computing geometric mean;
  • New helper function hm_mean() for computing harmonic mean;
  • New helper function Huehn() for computing Huehn’s stability statistic;
  • New helper function Thennasaru() for computing Thennasaru’s stability statistic;
  • Improve usability of get_model_data() by supporting new classes of models;
  • Update function’s documentation;
  • Update vignettes;

metan 1.0.1 Unreleased

  • 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 documentation;
  • Update vignettes;

metan 1.0.0 Unreleased

The changes in this version were made based on suggestions received when metan was submitted to CRAN for the first time.

Minor changes

To allow automatic testing, the examples of the following functions were unwrapped by deleting \dontrun{}.

In the examples of the functions for cross-validation \dontrun{} was changed with \donttest{}

metan 0.2.0 Unreleased

This is the first version that will be submitted to CRAN. In this version, deprecated functions in the last versions were defunct. Some new features were implemented.

metan 0.1.5 Unreleased

In the latest development version, the package METAAB was renamed to metan (multi-environment trials analysis). Aiming at a cleaner coding, in this version, some functions were deprecated and will be defunct in the near future. Alternative functions were implemented.

  • For WAAS.AMMI(), use waas().
  • For WAASBYratio(), use wsmp().
  • For WAASratio.AMMI(), use wsmp().
  • For autoplot.WAAS.AMMI(), use autoplot.waas().
  • For plot.WAASBYratio(), use plot.wsmp().
  • For plot.WAASratio.AMMI(), use plot.wsmp().
  • For predict.WAAS.AMMI(), use predict.waas().
  • For summary.WAAS.AMMI(), use summary.waas()

Widely-known parametric and nonparametric methods were implemented, using the following functions.

  • Annicchiarico() to compute the genotypic confidence index.
  • ecovalence() to compute the Wricke’s ecovalence.
  • ge_factanal() to compute to compute the stability and environmental.
  • ge_reg() to compute the joint-regression analysis. stratification using factor analysis.
  • superiority() to compute the nonparametric superiority index.

METAAB 0.1.4 Unreleased

In the latest development version, some useful functions were included. One of the most interesting features included in this version was allowing the functions to receive data from the forward-pipe operator %>%. Bellow are the functions included in this version.

  • anova_ind() to perform a within-environment analysis of variance easily;
  • colindiag() to perform a collinearity diagnostic of a set of predictors;a
  • find_outliers() to easily find possible outliers in the dataset;
  • group_factors() to split a dataset into a list of subsets using one or more grouping factors. This function may be used befor some functions, e.g., find_outliers(), colindiag(), path_coeff() to compute the statistics for each level of the factor (or combination of levels of factors).
  • lpcor() to compute linear and partial correlation coefficients.
  • pairs_mantel() to compute a graphic pairwise Mantel’s test using a set of correlation matrices;
  • path_coeff() to compute path coefficients with minimal multicollinearity;

The following S3 Methods were also implemented:

  • is.group_factors() and as.group_factors() to check or easily coerce a dataframe that has one or more factor columns to an object of group_factors;
  • is.lpcorr() and as.lpcorr() to check or easily coerce a list of correlation matrices to an object of lpcorr;

METAAB 0.1.3 Unreleased

  • AMMI-based stability indexes;
  • Allow analyzing multiple variables at the same time;
  • S3 methods such as plot(), predict(), summary() implemented.

METAAB 0.1.2 Unreleased

  • Mixed-effect model with environment random effect;
  • Random-effect model.

METAAB 0.1.1 Unreleased

  • The first version of the package