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.

Asks Yes-No questions with variable or custom responses.

Compute the standard expected years of life lost (YLL), as developed by the Global Burden of Disease Study (Murray, C.J., Lopez, A.D. and World Health Organization, 1996). The YLL is based on comparing the age of death to an external standard life expectancy curve. It also computes the average YLL, which highlights premature causes of death and brings attention to preventable deaths (Aragon et al., 2008).

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.

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.

This package provides a collection of lightweight helper functions (imps) both for interactive use and for inclusion within other packages. These include functions for minimal input assertions, visualising colour palettes, quoting user input, searching rows of a data frame and capturing string tokens.

Modelling the yield curve with some parametric models. The models implemented are: Nelson, C.R., and A.F. Siegel (1987) <doi: 10.1086/296409>, Diebold, F.X. and Li, C. (2006) <doi: 10.1016/j.jeconom.2005.03.005> and Svensson, L.E. (1994) <doi: 10.3386/w4871>. The package also includes the data of the term structure of interest rate of Federal Reserve Bank and European Central Bank.

Simulation and Inference for SDEs and Other Stochastic Processes.

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.

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.

This package provides a YAML-based mechanism for working with table metadata. Supports compact syntax for creating, modifying, viewing, exporting, importing, displaying, and plotting metadata coded as column attributes. The yamlet dialect is valid YAML with defaults and conventions chosen to improve readability. See ?yamlet, ?decorate, ?modify, ?io_csv, and ?ggplot.decorated.

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).

Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with baseline hazard/odds modeled with Bernstein polynomials. Details about the model can be found in Demarqui et al. (2019) <arXiv:1910.04475>. Model fitting can be carried out via both maximum likelihood and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.

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.

An extension for NetSurfP-2.0 (Klausen et al. (2019) <doi:10.1002/prot.25674>) which is specifically designed to analyze the results of bottom-up-proteomics that is primarily analyzed with MaxQuant (Cox, J., Mann, M. (2008) <doi:10.1038/nbt.1511>). This tool is designed to process a large number of yeast peptides that produced as a results of whole yeast cell-proteome digestion and provide a coherent picture of secondary structure of proteins.

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.

Write YAML front matter for R Markdown and related documents. Work with YAML objects more naturally and write the resulting YAML to your clipboard or to YAML files related to your project.

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>).

This package provides a graphical user interface for the yuima package.

This package provides a fast, correct, safe, and ergonomic YAML 1.2 parser and generator written in Rust'. Convert between YAML and simple R objects with full support for multi-document streams, tags, anchors, and aliases. Offers opt-in handlers for custom tag behavior and round-trips common R data structures. Implements the YAML 1.2.2 specification from the YAML Language Development Team (2021) <https://yaml.org/spec/1.2.2/>. Proudly supported by Posit.

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>.