This package provides a function to calculate infinite-jackknife-based standard errors for fixed effects parameters in brms models, handling both clustered and independent data. References: Ji et al. (2024) <doi:10.48550/arXiv.2407.09772>; Giordano et al. (2024) <doi:10.48550/arXiv.2305.06466>.

Convert files to and from IDX format to vectors, matrices and arrays. IDX is a very simple file format designed for storing vectors and multidimensional matrices in binary format. The format is described on the website from Yann LeCun <http://yann.lecun.com/exdb/mnist/>.

This package provides functions for analyzing multiple choice items. These analyses include the convertion of student response into binaty data (correct/incorrect), the computation of the number of corrected responses and grade for each subject, the calculation of item difficulty and discrimination, the computation of the frecuency and point-biserial correlation for each distractor and the graphical analysis of each item.

Introductory statistics methods to accompany "Investigating Statistical Concepts, Applications, and Methods" (ISCAM) by Beth Chance & Allan Rossman (2024) <https://rossmanchance.com/iscam4/>. Tools to introduce statistical concepts with a focus on simulation approaches. Functions are verbose, designed to provide ample output for students to understand what each function does. Additionally, most functions are accompanied with plots. The package is designed to be used in an educational setting alongside the ISCAM textbook.

Integrated toolbox supporting common file formats used for intracranial Electroencephalography (iEEG) and deep-brain stimulation (DBS) study.

Currently used CI method has its limitation when the test statistics are asymmetrical (chi-square test, F-test) or the model functions are non-linear. It can be overcome by using the likelihood functions for the interval estimation. inteli package now supports interval estimation for the mean, variance, variance ratio, binomial distribution, Poisson distribution, odds ratio, risk difference, relative risk and their likelihood function plots. Testing functions are also provided.

Download and manage data sets of statistical projects and geographic data created by Instituto Nacional de Estadistica y Geografia (INEGI). See <https://www.inegi.org.mx/>.

This package provides implementation of various correlation coefficients of common use in Information Retrieval. In particular, it includes Kendall (1970, isbn:0852641990) tau coefficient as well as tau_a and tau_b for the treatment of ties. It also includes Yilmaz et al. (2008) <doi:10.1145/1390334.1390435> tauAP correlation coefficient, and versions tauAP_a and tauAP_b developed by Urbano and Marrero (2017) <doi:10.1145/3121050.3121106> to cope with ties.

This package provides a variety of methods for estimating intrinsic dimension of data sets (i.e the manifold or Hausdorff dimension of the support of the distribution that generated the data) as reviewed in Johnsson, K. (2016, ISBN:978-91-7623-921-6) and Johnsson, K., Soneson, C. and Fontes, M. (2015) <doi:10.1109/TPAMI.2014.2343220>. Furthermore, to evaluate the performance of these estimators, functions for generating data sets with given intrinsic dimensions are provided.

Facilitates the calculation of 40 different insulin sensitivity indices based on fasting, oral glucose tolerance test (OGTT), lipid (adipose), tracer (palmitate and glycerol rate), and DXA (fat mass) measurement values. Enables easy and accurate assessment of insulin sensitivity, critical for understanding and managing metabolic disorders like diabetes and obesity. Indices calculated are described in Gastaldelli (2022) <doi:10.1002/oby.23503>, Suleman (2024) <doi:10.1210/clinem/dgae275>, and Lorenzo (2010) <doi:10.1210/jc.2010-1144>.

Estimate the orientation of an inertial measurement unit (IMU) with a 3-axis accelerometer and a 3-axis gyroscope using a complementary filter. imuf takes an IMU's accelerometer and gyroscope readings, time duration, its initial orientation, and a gain factor as inputs, and returns an estimate of the IMU's final orientation.

This package provides a comprehensive toolkit for intraclass correlation coefficient (ICC) analysis, integrating three core functionalities: (1) Closed-form sample size calculation for ICC estimation with assurance probability, based on Zou (2012) <doi:10.1002/sim.5466>; (2) Full implementation of all 10 ICC types (6 common + 4 supplementary) for point estimation, exact confidence interval calculation, and formal hypothesis testing, following the methods of McGraw & Wong (1996) <doi:10.1037/1082-989X.1.1.30> and the standard decision framework; (3) An interactive shiny application that guides users through ICC type selection, performs calculations, and provides reliability evaluation based on the Koo & Li (2016) <doi:10.1016/j.jcm.2016.02.012> criteria. Compared to existing packages, it provides a unified decision workflow and supports all less common ICC variants.

This package provides tools for easily and flexibly creating ggplot2 maps with inset maps. One crucial feature of maps is that they have fixed coordinate ratios, i.e., they cannot be distorted, which makes it difficult to manually place inset maps. This package provides functions to automatically position inset maps based on user-defined parameters, making it extremely easy to create maps with inset maps with minimal code.

This package provides native R access to Interactive Brokers Trader Workstation API.

An R client for the ipbase.com IP Geolocation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://ipbase.com/docs> .

Interactive plots for R.

This package provides a set of tools for evaluating several measures of case influence for structural equation models.

This package provides a collection of intuitive and user-friendly functions for computing confidence intervals for common statistical tasks, including means, differences in means, proportions, and odds ratios. The package also includes tools for linear regression analysis and several real-world datasets intended for teaching and applied statistical inference.

Allows the construction selection indices based on estimated breeding values in animal and plant breeding and to calculate several analytic measures around to assess its impact on genetic and phenotypic progress. The methodology thereby allows to analyze genetic gain of traits in the breeding goal which are not part of the actual index and automatically computes several analytic measures. It further allows to retrospectively derive realized economic weights from observed genetic trends. The framework is described in Simianer, H., Heise, J., Rensing, S., Pook, T. Geibel, J. and Reimer, C. (2023) <doi:10.1186/s12711-023-00807-0>.

Calculates various intraclass correlation coefficients used to quantify inter-rater and intra-rater reliability. The assumption here is that the raters produced quantitative ratings. Most of the statistical procedures implemented in this package are described in details in Gwet, K.L. (2014, ISBN:978-0970806284): "Handbook of Inter-Rater Reliability," 4th edition, Advanced Analytics, LLC.

Facilitates the calculation of validated pancreatic islet hormone-release indices from fasting and oral glucose tolerance test (OGTT) measurements. Provides beta-cell insulin release indices (including HOMA-beta, corrected insulin response, Stumvoll first-phase index, BIGTT-AIR, and disposition indices) as described in Madsen (2024) <doi:10.1038/s42255-024-01140-6>, alongside alpha-cell glucagon release and glucagon resistance indices derived from the glucagon-suppression and liver-alpha-cell-axis literature. Enables reproducible assessment of beta-cell and alpha-cell function for metabolic and endocrine research.

Estimation of the most-left informative set of gross returns (i.e., the informative set). The procedure to compute the informative set adjusts the method proposed by Mariani et al. (2022a) <doi:10.1007/s11205-020-02440-6> and Mariani et al. (2022b) <doi:10.1007/s10287-022-00422-2> to gross returns of financial assets. This is accomplished through an adaptive algorithm that identifies sub-groups of gross returns in each iteration by approximating their distribution with a sequence of two-component log-normal mixtures. These sub-groups emerge when a significant change in the distribution occurs below the median of the financial returns, with their boundary termed as the â change point" of the mixture. The process concludes when no further change points are detected. The outcome encompasses parameters of the leftmost mixture distributions and change points of the analyzed financial time series. The functionalities of the INFOSET package include: (i) modelling asset distribution detecting the parameters which describe left tail behaviour (infoset function), (ii) clustering, (iii) labeling of the financial series for predictive and classification purposes through a Left Risk measure based on the first change point (LR_cp function) (iv) portfolio construction (ptf_construction function). The package also provide a specific function to construct rolling windows of different length size and overlapping time.

This package performs Invariant Coordinate Selection (ICS) (Tyler, Critchley, Duembgen and Oja (2009) <doi:10.1111/j.1467-9868.2009.00706.x>) and especially ICS for multivariate outlier detection with application to quality control (Archimbaud, Nordhausen, Ruiz-Gazen (2018) <doi:10.1016/j.csda.2018.06.011>) using a shiny app.

Implementation of functions to assign corresponding common job prestige scores (SIOPS, ISEI), the official job or group title and the ISCO-88 code to given ISCO-08 codes. ISCO-08 is the latest version of the International Standard Classification of Occupations which is used to organise information on labour and jobs.