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roll - Rolling and Expanding Statistics

Fast and efficient computation of rolling and expanding statistics for time-series data. The default algorithm in the 'roll' package is an online algorithm that, as observations are added to and removed from a window, updates statistics and discards observations from memory (Welford, 1962, <doi:10.1080/00401706.1962.10490022>; West, 1979, <doi:10.1145/359146.359153>); as a result, the amount of time to evaluate each function is significantly shorter as the computation is independent of the window. In contrast, an offline algorithm requires all observations in memory to calculate the statistic for each window, so users can trade speed for accuracy and select the offline algorithm by setting the online argument to FALSE. Quantiles are computed from the inverse of the empirical distribution function with averaging at discontinuities (Hyndman and Fan, 1996, <doi:10.1080/00031305.1996.10473566>). Use cases include rolling summary statistics, time-varying relationships between variables, and feature engineering for forecasting and signal construction. The package supports rolling and expanding windows, weights, and handling of missing values via the min_obs, complete_obs, and na_restore arguments. The implementation uses 'RcppParallel' to parallelize the online algorithms across columns and the offline algorithms across windows.

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algorithmsrcppstatisticsopenblascppopenmp

9.80 score 118 stars 11 dependents 398 scripts 4.5k downloads

yfscreen - Yahoo Finance 'screener' API

Simple and efficient access to Yahoo Finance's 'screener' API <https://finance.yahoo.com/research-hub/screener/> for querying and retrieving financial data. The 'yfscreen' package 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 such as equities, mutual funds, ETFs, indices, and futures. The package supports advanced query capabilities, including logical operators, nested filters, and customizable payloads. It handles pagination automatically, fetching results in batches of up to 250 entries per request for efficient retrieval of large datasets. Filters can be defined dynamically to support a wide range of screening needs. The implementation uses standard HTTP libraries to handle API interactions efficiently and is available in both R and 'Python' for accessibility to a broad audience.

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datapython

5.06 score 19 stars 4 scripts 533 downloads

rollshap - Rolling Shapley Values

Analytical computation of rolling and expanding Shapley values for time-series data. The 'rollshap' package decomposes the coefficient of determination (R-squared) of a linear regression into nonnegative contributions from each explanatory variable using the Shapley value from cooperative game theory (Shapley, 1953, <doi:10.1515/9781400881970-018>). For each window, the exact Shapley value is computed by fitting all subsets of the explanatory variables and averaging the marginal contribution to R-squared across all orderings, which returns an order-invariant attribution that sums to the full-model R-squared. Use cases include variable importance, factor attribution, and feature selection in time-series regression. The package supports rolling and expanding windows, weights, and handling of missing values via the min_obs, complete_obs, and na_restore arguments. The implementation uses the online and offline algorithms from the 'roll' package to compute rolling and expanding cross-products efficiently, with parallelism across columns and windows provided by 'RcppParallel'.

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algorithmsrcppshapleyopenblascppopenmp

4.29 score 3 stars 2 scripts 217 downloads

yfhist - Yahoo Finance 'history' API

Simple and efficient access to Yahoo Finance's 'history' API <https://finance.yahoo.com/> for querying and retrieving financial data. 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 retrieving historical data across a range of security types such as equities and ETFs, indices, and other tickers. The package supports flexible query capabilities, including customizable date ranges, multiple time intervals, and automatic data validation. It manages interval-specific limitations automatically, such as lookback periods for intraday data and maximum date ranges for minute-level intervals. The implementation uses standard HTTP libraries to handle API interactions efficiently and is available in both R and 'Python' for accessibility to a broad audience.

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3.98 score 1 stars 2 scripts 124 downloads

rolloptim - Rolling Optimizations

Analytical computation of rolling optimization for time-series data. The 'rolloptim' package solves constrained quadratic and linear programs in closed form by applying Lagrangian multipliers and the Karush-Kuhn-Tucker conditions (Kuhn and Tucker, 1951, <doi:10.1525/9780520411586-036>) to perform mean-variance portfolio optimization (Markowitz, 1952, <doi:10.1111/j.1540-6261.1952.tb01525.x>) over rolling windows. For each window, the analytical solution computes the optimal weights that minimize variance, maximize expected return, minimize residual sum of squares, or maximize quadratic utility, subject to a total-weight equality constraint and box bounds on each weight. Use cases include mean-variance portfolio optimization, expected-return maximization, and constrained regression. The package supports rolling optimizations with constraints via the total, lower, and upper arguments. The implementation accepts rolling moments computed via the 'roll' package and uses 'RcppArmadillo' for linear algebra, with parallelism across windows provided by 'RcppParallel'.

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algorithmsoptimizationrcppopenblascppopenmp

3.41 score 4 stars 4 scripts

rolleigen - Rolling Eigenanalysis

Fast and efficient computation of rolling and expanding eigenanalysis for time-series data. The 'rolleigen' package decomposes the covariance matrix of the explanatory variables into eigenvalues and eigenvectors to perform principal component analysis (Pearson, 1901, <doi:10.1080/14786440109462720>; Hotelling, 1933, <doi:10.1037/h0071325>) and principal component regression (Massy, 1965, <doi:10.1080/01621459.1965.10480787>) over rolling and expanding windows. For each window, the eigenvalues and eigenvectors are computed from the covariance matrix and, optionally, ordered from largest to smallest to summarize the directions of greatest variation in the data. A subset of leading components is then used to fit a regression that mitigates collinearity in the explanatory variables. Use cases include dimensionality reduction, factor extraction, and regression on collinear explanatory variables. The package supports rolling and expanding windows, weights, and handling of missing values via the min_obs, complete_obs, and na_restore arguments. The implementation uses the online and offline algorithms from the 'roll' package to compute rolling and expanding cross-products efficiently, with parallelism across columns and windows provided by 'RcppParallel'.

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algorithmseigenrcppopenblascppopenmp

3.18 score 3 stars 2 scripts

rolltalk - Rolling and Expanding Statistics Presentation

Presentation of rolling and expanding statistics for time-series data. The 'rolltalk' package demonstrates the rolling and expanding statistics of the 'roll' package in a 'Quarto' presentation that is rendered to a PDF file with the roll_talk() function.

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algorithmspresentationquartostatistics

2.95 score 3 stars 1 scripts

rolleda - Rolling Exploratory Data Analysis

Exploratory data analysis of rolling statistics for time-series data. The 'rolleda' package explores the rolling statistics of the 'roll' package in a 'Shiny' web application that is launched with the roll_eda() function.

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analysisapplicationshiny

2.88 score 3 stars 1 scripts