Kevin Alejandro Pérez Mendoza

Luisa Gomez Camargo

Tablero con distribuciones normales y exponenciales

Gallery showcasing various plots generated with the visualFields package. Explore the range of visualization options available for visual field data analysis.

Presentation for N-gram next word predictor developed using Shinyapp

This exercise explores four methods for assigning positions within consecutive, repeated elements in a vector, efficiently labeling sequences of a target value while keeping other values unchanged. For example, given a vector like 0 0 0 1 1 1 1 0 0 1 1 0 0 0 1 1 1 1 0 0 0 0 0, the desired output is 0 0 0 1 2 3 4 0 0 1 2 0 0 0 1 2 3 4 0 0 0 0 0, a need that arises in various applications such as time series analysis (identifying trends and patterns in sequential data), genomic sequence processing (assigning positions in repeated nucleotides or amino acid sequences), and text data manipulation (detecting and processing repeated words, phrases, or characters). To address these diverse use cases, I developed generalized function versions for four different methods and tested their efficiency across vectors of varying lengths, scaling up to 1 × 10⁶ elements (Figs. 1 and 2). The key takeaways are: 1. Different approaches yield the same result with varying trade-offs in efficiency, readability, and flexibility. 2. rle is the best choice when speed is critical. 3. Benchmarking is essential for selecting methods in large-scale data processing. 4. Alternative implementations not covered here may further optimize performance.