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.

For any spending function specified by the user, this package provides corresponding boundaries for interim testing using the adaptively weighted log-rank test developed by Yang and Prentice (2010 <doi:10.1111/j.1541-0420.2009.01243.x>). The package uses a re-sampling method to obtain stopping boundaries at the interim looks.The output consists of stopping boundaries and observed values of the test statistics at the interim looks, along with nominal p-values defined as the probability of the test exceeding the specific observed test statistic value or critical value, regardless of the test behavior at other looks. The asymptotic validity of the stopping boundaries is established in Yang (2018 <doi:10.1002/sim.7958>).

Inference procedures accommodate a flexible range of hazard ratio patterns with a two-sample semi-parametric model. This model contains the proportional hazards model and the proportional odds model as sub-models, and accommodates non-proportional hazards situations to the extreme of having crossing hazards and crossing survivor functions. Overall, this package has four major functions: 1) the parameter estimation, namely short-term and long-term hazard ratio parameters; 2) 95 percent and 90 percent point-wise confidence intervals and simultaneous confidence bands for the hazard ratio function; 3) p-value of the adaptive weighted log-rank test; 4) p-values of two lack-of-fit tests for the model. See the included "read_me_first.pdf" for brief instructions. In this version (1.1), there is no need to sort the data before applying this package.

An implementation of equilibrium-based yield per recruit methods. Yield per recruit methods can used to estimate the optimal yield for a fish population as described by Walters and Martell (2004) <isbn:0-691-11544-3>. The yield can be based on the number of fish caught (or harvested) or biomass caught for all fish or just large (trophy) individuals.

This package provides a number of functions to facilitate extracting information in YAML fragments from one or multiple files, optionally structuring the information in a data.tree'. YAML (recursive acronym for "YAML ain't Markup Language") is a convention for specifying structured data in a format that is both machine- and human-readable. YAML therefore lends itself well for embedding (meta)data in plain text files, such as Markdown files. This principle is implemented in yum with minimal dependencies (i.e. only the yaml packages, and the data.tree package can be used to enable additional functionality).

Setting layout through YAML headers in R-Markdown documents, enabling their automatic generation. Functions and methods may summarize R objects in automatic reports, for instance check-lists and further reports applied to the packages taxlist and vegtable'.

Simplify working with the YouTube Analytics API <https://developers.google.com/youtube/analytics>. Collect data for your channel including geography, traffic sources, time period, etc.

Nonparametric estimation of discount functions and yield curves from transaction data of coupon paying bonds. Koo, B., La Vecchia, D., & Linton, O. B. (2021) <doi:10.1016/j.jeconom.2020.04.014> describe an application of this package using the Center for Research in Security Prices (CRSP) Bond Data and document its implementation.

Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with piecewise exponential baseline distribution. Details about the model can be found in Demarqui and Mayrink (2019) <arXiv:1910.02406>. Model fitting carried out via likelihood-based and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.

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.

Download financial market data, company information, financial statements, options data, and more from the unofficial Yahoo Finance API.

Asks Yes-No questions with variable or custom responses.

Analyze data from behavioral experiments conducted using MED-PC software developed by Med Associates Inc. Includes functions to fit exponential and hyperbolic models for delay discounting tasks, exponential mixtures for inter-response times, and Gaussian plus ramp models for peak procedure data, among others. For more details, refer to Alcala et al. (2023) <doi:10.31234/osf.io/8aq2j>.

Connects R to Zotero through the Better BibTeX for Zotero connector <https://retorque.re/zotero-better-bibtex/>. Provides functions to insert in-text citations and bibliography entries directly into documents, detect citations already present in R Markdown and Quarto files, and synchronise bibliography files. Includes an RStudio addin for interactive use.

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).

Simulation, exploratory data analysis and Bayesian analysis of the p-order Integer-valued Autoregressive (INAR(p)) and Zero-inflated p-order Integer-valued Autoregressive (ZINAR(p)) processes, as described in Garay et al. (2020) <doi:10.1080/00949655.2020.1754819>.

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>.

Estimation methods for zero-inflated Poisson factor analysis (ZIPFA) on sparse data. It provides estimates of coefficients in a new type of zero-inflated regression. It provides a cross-validation method to determine the potential rank of the data in the ZIPFA and conducts zero-inflated Poisson factor analysis based on the determined rank.

This package provides functions to compute compositional turnover using zeta-diversity, the number of species shared by multiple assemblages. The package includes functions to compute zeta-diversity for a specific number of assemblages and to compute zeta-diversity for a range of numbers of assemblages. It also includes functions to explain how zeta-diversity varies with distance and with differences in environmental variables between assemblages, using generalised linear models, linear models with negative constraints, generalised additive models,shape constrained additive models, and I-splines.

An implementation of z-curves - a method for estimating expected discovery and replicability rates on the bases of test-statistics of published studies. The package provides functions for fitting the density, EM, and censored EM version (Bartoš & Schimmack, 2022, <doi:10.15626/MP.2021.2720>; Schimmack & Bartoš, 2023, <doi: 10.1371/journal.pone.0290084>), as well as the original density z-curve (Brunner & Schimmack, 2020, <doi:10.15626/MP.2018.874>). Furthermore, the package provides summarizing and plotting functions for the fitted z-curve objects. See the aforementioned articles for more information about the z-curves, expected discovery and replicability rates, validation studies, and limitations.

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>.

An interface to Zonation software, enabling users to run spatial conservation prioritization workflows in R'. It streamlines input preparation, execution, and post-processing, while supporting reproducibility and lowering the entry barrier for learning, teaching, and research in conservation planning. The methods implemented in Zonation are described in Moilanen et al. (2022) <doi:10.1111/2041-210X.13819>.

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.

This package implements a grid search algorithm with an adaptive zooming strategy for global optimisation problems with multiple local optima. The method recursively refines the search region around promising grid points, providing reliable initial values for subsequent optimisation procedures. The algorithm is computationally efficient in moderate- to high-dimensional settings.