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>).

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

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 collection of data exploration tools was developed at Yale University for the graphical exploration of complex multivariate data; barcode and gpairs now have their own packages. The big.read.table() function provided here may be useful for large files when only a subset is needed (but please see the note in the help page for this function).

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.

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.

The purpose of this package is to provide methods to interpret multiple linear regression and canonical correlation results including beta weights,structure coefficients, validity coefficients, product measures, relative weights, all-possible-subsets regression, dominance analysis, commonality analysis, and adjusted effect sizes.

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.

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.

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.

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.

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.

This package provides a fast JSON parser, generator and validator which converts JSON', NDJSON (Newline Delimited JSON') and GeoJSON (Geographic JSON') data to/from R objects. The standard R data types are supported (e.g. logical, numeric, integer) with configurable handling of NULL and NA values. Data frames, atomic vectors and lists are all supported as data containers translated to/from JSON'. GeoJSON data is read in as simple features objects. This implementation wraps the yyjson C library which is available from <https://github.com/ibireme/yyjson>.

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.

Fits yield curves using Nelson-Siegel (1987) <doi:10.1086/296409>, Svensson (1994) <doi:10.3386/w4871>, and cubic spline methods. Extracts forward rates, discount factors, and par rates from fitted curves. Computes duration and convexity risk measures. Computes Z-spread and key rate durations. Provides principal component decomposition following Litterman and Scheinkman (1991) <doi:10.3905/jfi.1991.692347>, carry and roll-down analysis, and slope measures. All methods are pure computation with no external dependencies beyond base R; works with yield data from any source.

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'.

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.

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.

This package provides with parametric Risk Neutral Densities (RNDs) and cumulative densities of futures prices on fixed-income products. It relies on options on Short Term Interest Rate futures or options on government bond futures. It models the futures price as a mixture of lognormal densities. It also provides with the RNDs and cumulative densities of the money market rate or the government bond yield inferred from the futures price, using the RND of the futures price. It eventually provides with the probability attached to each bond in the delivery basket of a government bond futures to be the cheapest at maturity, using the RND of the bond futures price. The package leverages on the works of Melick, W. R. and Thomas, C. P. (1997) <doi:10.2307/2331318> and B. Bahra (1998) <doi:10.2139/ssrn.77429>.

This package provides covariate-adjusted comparison of two groups of right censored data, where the binary group variable has separate short-term and long-term effects on the hazard function, while effects of covariates such as age, blood pressure, etc. are proportional on the hazard. The model was studied in Yang and Prentice (2015) <doi:10.1002/sim.6453> and it extends the two sample version of the short-term and long-term hazard ratio model proposed in Yang and Prentice (2005) <doi:10.1093/biomet/92.1.1>. The model extends the usual Cox proportional hazards model to allow more flexible hazard ratio patterns, such as gradual onset of effect, diminishing effect, and crossing hazard or survival functions. This package provides the following: 1) point estimates and confidence intervals for model parameters; 2) point estimate and confidence interval of the average hazard ratio; and 3) plots of estimated hazard ratio function with point-wise and simultaneous confidence bands.

This package performs nearest neighbor-based imputation using one or more alternative approaches to processing multivariate data. These include methods based on canonical correlation: analysis, canonical correspondence analysis, and a multivariate adaptation of the random forest classification and regression techniques of Leo Breiman and Adele Cutler. Additional methods are also offered. The package includes functions for comparing the results from running alternative techniques, detecting imputation targets that are notably distant from reference observations, detecting and correcting for bias, bootstrapping and building ensemble imputations, and mapping results.

Asks Yes-No questions with variable or custom responses.

Determines the sum of squares of the (2^n)-1 factorial effects in a 2^n factorial experiment using Yates algorithm.

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.