The Author's personal R Package that contains miscellaneous functions. The current version of package contains miscellaneous functions for brain data to compute Asymmetry Index (AI) and bilateral (L+R) measures and reshape the data.

This package provides a collection of string functions designed for writing compact and expressive R code. yasp (Yet Another String Package) is simple, fast, dependency-free, and written in pure R. The package provides: a coherent set of abbreviations for paste() from package base with a variety of defaults, such as p() for "paste" and pcc() for "paste and collapse with commas"; wrap(), bracket(), and others for wrapping a string in flanking characters; unwrap() for removing pairs of characters (at any position in a string); and sentence() for cleaning whitespace around punctuation and capitalization appropriate for prose sentences.

Another implementation of general regression neural network in R based on Specht (1991) <DOI:10.1109/72.97934>. It is applicable to the functional approximation or the classification.

Simple and efficient access to Yahoo Finance's historical data API <https://finance.yahoo.com/> for querying and retrieval of financial data. The core functionality of the yfhist package abstracts the complexities of interacting with Yahoo Finance APIs, such as session management, crumb and cookie handling, query construction, date validation, and interval management. This abstraction allows users to focus on retrieving data rather than managing API details. Use cases include historical data across a range of security types including equities & ETFs, indices, and other tickers. The package supports flexible query capabilities, including customizable date ranges, multiple time intervals, and automatic data validation. It automatically manages interval-specific limitations, such as lookback periods for intraday data and maximum date ranges for minute-level intervals. The implementation leverages standard HTTP libraries to handle API interactions efficiently and provides support for both R and Python to ensure accessibility for a broad audience.

Procedures to perform consensus clustering starting from a dissimilarity matrix or a data matrix. It's allowed to select if the subsampling has to be by samples or features. In case of computational heavy load, the procedures can run in parallel.

Convert YMD format number or string to Date efficiently, using Rust's standard library. It also provides helper functions to handle Date, e.g., quick finding the beginning or end of the given period, adding months to Date, etc.

The generalized construction methods for magic squares, inspired by the ancient Chinese mathematician Yang Hui's classical work "Xu Gu Zhai Qi Suan Fa". These methods can construct 4n-order magic squares and 2(2n+1)-order magic squares.

This package provides helper functions to perform Bayesian model averaging using Markov chain Monte Carlo samples from separate models. Calculates weights and obtains draws from the model-averaged posterior for quantities of interest specified by the user. Weight calculations can be done using marginal likelihoods or log-predictive likelihoods as in Ando, T., & Tsay, R. (2010) <doi:10.1016/j.ijforecast.2009.08.001>.

Simple and efficient access to Yahoo Finance's screener API <https://finance.yahoo.com/research-hub/screener/> for querying and retrieval of financial data. The core functionality abstracts the complexities of interacting with Yahoo Finance APIs, such as session management, crumb and cookie handling, query construction, pagination, and JSON payload generation. This abstraction allows users to focus on filtering and retrieving data rather than managing API details. Use cases include screening across a range of security types including equities, mutual funds, ETFs, indices, and futures. The package supports advanced query capabilities, including logical operators, nested filters, and customizable payloads. It automatically handles pagination to ensure efficient retrieval of large datasets by fetching results in batches of up to 250 entries per request. Filters can be dynamically defined to accommodate a wide range of screening needs. The implementation leverages standard HTTP libraries to handle API interactions efficiently and provides support for both R and Python to ensure accessibility for a broad audience.

Simulation and Inference for SDEs and Other Stochastic Processes.

Test of linearity originally proposed by Yatchew (1997) <doi:10.1016/S0165-1765(97)00218-8> and improved by de Chaisemartin & D'Haultfoeuille (2024) <doi:10.2139/ssrn.4284811> to be robust under heteroskedasticity.

Facilitates download of financial data from Yahoo Finance <https://finance.yahoo.com/>, a vast repository of stock price data across multiple financial exchanges. The package offers a local caching system and support for parallel computation.

This package provides an R wrapper for the Zendesk API.

Statistical models and utilities for the analysis of word frequency distributions. The utilities include functions for loading, manipulating and visualizing word frequency data and vocabulary growth curves. The package also implements several statistical models for the distribution of word frequencies in a population. (The name of this package derives from the most famous word frequency distribution, Zipf's law.).

Generates Realizations of First-Order Integer Valued Autoregressive Processes with Zero-Inflated Innovations (ZINAR(1)) and Estimates its Parameters as described in Garay et al. (2021) <doi:10.1007/978-3-030-82110-4_2>.

This package provides a set of functions for working with American postal codes, which are known as ZIP Codes. These include accessing ZIP Code to ZIP Code Tabulation Area (ZCTA) crosswalks, retrieving demographic data for ZCTAs, and tabulating demographic data for three-digit ZCTAs.

Facilitates making a connection to the Zendesk API and executing various queries. You can use it to get ticket, ticket metrics, and user data. The Zendesk documentation is available at <https://developer.zendesk.com/rest_api /docs/support/introduction>. This package is not supported by Zendesk (owner of the software).

This tool provides functions to load, segment and classify zooplankton images. The image processing algorithms and the machine learning classifiers in this package are (will be, since these have not been added yet) direct ports of an early python implementation that can be found at <https://github.com/arickGrootveld/ZooID>. The model weights and datasets (also not added yet) that are a part of this package can also be found at Arick Grootveld, Eva R. Kozak, Carmen Franco-Gordo (2023) <doi:10.5281/zenodo.7979996>.

Permutations tests to identify factor correlated to zero-inflated proportions response. Provide a performance indicator based on Spearman correlation to quantify the part of correlation explained by the selected set of factors. See details for the method at the following preprint e.g.: <https://hal.archives-ouvertes.fr/hal-02936779v3>.

Facilitates making a connection to the Zoom API and executing various queries. You can use it to get data on Zoom webinars and Zoom meetings. The Zoom documentation is available at <https://developers.zoom.us/docs/api/>. This package is not supported by Zoom (owner of the software).

Empowers users to fuzzily-merge data frames with millions or tens of millions of rows in minutes with low memory usage. The package uses the locality sensitive hashing algorithms developed by Datar, Immorlica, Indyk and Mirrokni (2004) <doi:10.1145/997817.997857>, and Broder (1998) <doi:10.1109/SEQUEN.1997.666900> to avoid having to compare every pair of records in each dataset, resulting in fuzzy-merges that finish in linear time.

The zlib package for R aims to offer an R-based equivalent of Python's built-in zlib module for data compression and decompression. This package provides a suite of functions for working with zlib compression, including utilities for compressing and decompressing data streams, manipulating compressed files, and working with gzip', zlib', and deflate formats.

Uses bootstrap to test zero order correlation being equal to a partial or semi-partial correlation (one or two tailed). Confidence intervals for the parameter (zero order minus partial) can also be determined. Implements the bias-corrected and accelerated bootstrap method as described in "An Introduction to the Bootstrap" Efron (1983) <0-412-04231-2>.

This package implements the estimation of local (and global) association measures: Lewontin's D, Ducher's Z, pointwise mutual information, normalized pointwise mutual information and chi-squared residuals. The significance of local (and global) association is accessed using p-values estimated by permutations.