Research Assessment Tools

Includes algorithms to assess research productivity and patterns, such as the h-index and i-index. Cardoso et al. (2022) Cardoso, P., Fukushima, C.S. & Mammola, S. (2022) Quantifying the internationalization and representativeness in research. Trends in Ecology and Evolution, 37: 725-728.

High Dimensional Discriminant Analysis

Performs linear discriminant analysis in high dimensional problems based on reliable covariance estimators for problems with (many) more variables than observations. Includes routines for classifier training, prediction, cross-validation and variable selection.

R as a Plotting Engine

Generate basic charts either by custom applications, or from a small script launched from the system console, or within the R console. Two ASCII text files are necessary: (1) The graph parameters file, which name is passed to the function 'rplotengine()'. The user can specify the titles, choose the type of the graph, graph output formats (e.g. png, eps), proportion of the X-axis and Y-axis, position of the legend, whether to show or not a grid at the background, etc. (2) The data to be plotted, which name is specified as a parameter ('data_filename') in the previous file. This data file has a tabulated format, with a single character (e.g. tab) between each column. Optionally, the file could include data columns for showing confidence intervals.

Test and Detection of Explosive Behaviors for Time Series

Provides the Augmented Dickey-Fuller test and its variations to check the existence of bubbles (explosive behavior) for time series, based on the article by Peter C. B. Phillips, Shuping Shi and Jun Yu (2015a) . Some functions may take a while depending on the size of the data used, or the number of Monte Carlo replications applied.

Converting Transport Data from GTFS Format to GPS-Like Records

Convert general transit feed specification (GTFS) data to global positioning system (GPS) records in 'data.table' format. It also has some functions to subset GTFS data in time and space and to convert both representations to simple feature format.

Efficient Estimation Under Staggered Treatment Timing

Efficiently estimates treatment effects in settings with randomized staggered rollouts, using tools proposed by Roth and Sant'Anna (2023) .

Conesa Colors Palette

Provides a collection of palettes designed to integrate with 'ggplot', reflecting the color schemes associated with 'ConesaLab'.

National Road Safety Observatory (ONSV) Styles for 'gt' Tables

Wrapper functions for customizing HTML tables from the 'gt' package to the ONSV style.

Curated Agentic Harnesses for R Professional Roles

A bootstrapper that launches a command-line coding agent of the user's choice in a terminal tab pre-configured for a professional R role. Each role is described by a curated harness: a subset of community skills, a system prompt, a folder layout, and quality gates. The package does not run an agent loop and does not call a language model; it discovers the chosen coder binary, generates its configuration, links the curated skills, and opens the terminal. Code written by the agent is run manually by the user, by design, so that every generated script passes through a human audit gate before execution.

Calculate Forest Dynamics

Determines the dynamics of tree species communities (mortality rates, recruitment, loss and gain in basal area, net changes and turnover). Important notes are a) The 'forest_df' argument (data) must contain the columns 'plot' (plot identification), 'spp' (species identification), DBH_1 (Diameter at breast height in first year of measure) and DBH_2 (Diameter at breast height in second year of measure). DBH_1 and DBH_2 must be numeric values; b) example input file in 'data(forest_df_example)'; c) The argument 'inv_time' represents the time between inventories, in years; d) The 'coord' argument must be of the type 'c(longitude, latitude)', with decimal degree values; e) Argument 'add_wd' represents a dataframe with wood density values (g cm-3) format with three columns ('genus', 'species', 'wd'). This argument is set to NULL by default, and if isn't provided, the wood density will be estimated with the getWoodDensity() function from the 'BIOMASS' package.