An implementation of the Otsu's Image Segmentation Method described in the paper: "A C++ Implementation of Otsu's Image Segmentation Method". The algorithm is explained at <doi:10.5201/ipol.2016.158>.

Estimates the intraclass correlation coefficient (ICC) for count data to assess repeatability (intra-methods concordance) and concordance (between-method concordance). In the concordance setting, the ICC is equivalent to the concordance correlation coefficient estimated by variance components. The ICC is estimated using the estimates from generalized linear mixed models. The within-subjects distributions considered are: Poisson; Negative Binomial with additive and proportional extradispersion; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial with additive and proportional extradispersion. The statistical methodology used to estimate the ICC with count data can be found in Carrasco (2010) <doi:10.1111/j.1541-0420.2009.01335.x>.

Improved methods based on inverse probability weighting and outcome regression for causal inference and missing data problems.

Implementation of tandem clustering with invariant coordinate selection with different scatter matrices and several choices for the selection of components as described in Alfons, A., Archimbaud, A., Nordhausen, K.and Ruiz-Gazen, A. (2024) <doi:10.1016/j.ecosta.2024.03.002>.

This package provides a set of utilities for manipulating index numbers series including chain-linking, re-referencing, and computing growth rates.

This package implements various novel and standard clustering statistics and other analyses useful for understanding the spread of infectious disease.

Call the data wrappers for Izmir Metropolitan Municipality's Open Data Portal. This will return all datasets formatted as Excel files (.csv or .xlsx), as well as datasets that require an API key.

The Indian Alien Flora Information (ILORA) database contains 14 invasion-relevant variables for 1388 alien plant species in India. The package enables exploration of the database using user-defined criteria. Using this package, users can retrieve variable-specific and species-level data from the database. The package also supports exploratory data analysis and visualization to give users an idea of the variables of interest. Further details about the database are available at <https://iloradb.wixsite.com/alienflora>.

Analyst oriented utility functions to handle the different quirks of the Israeli CBS municipal data, harmonize id's and bring together data points from different years.

Regression models for interval censored data. Currently supports Cox-PH, proportional odds, and accelerated failure time models. Allows for semi and fully parametric models (parametric only for accelerated failure time models) and Bayesian parametric models. Includes functions for easy visual diagnostics of model fits and imputation of censored data.

The marginal treatment effect was introduced by Heckman and Vytlacil (2005) <doi:10.1111/j.1468-0262.2005.00594.x> to provide a choice-theoretic interpretation to instrumental variables models that maintain the monotonicity condition of Imbens and Angrist (1994) <doi:10.2307/2951620>. This interpretation can be used to extrapolate from the compliers to estimate treatment effects for other subpopulations. This package provides a flexible set of methods for conducting this extrapolation. It allows for parametric or nonparametric sieve estimation, and allows the user to maintain shape restrictions such as monotonicity. The package operates in the general framework developed by Mogstad, Santos and Torgovitsky (2018) <doi:10.3982/ECTA15463>, and accommodates either point identification or partial identification (bounds). In the partially identified case, bounds are computed using either linear programming or quadratically constrained quadratic programming. Support for four solvers is provided. Gurobi and the Gurobi R API can be obtained from <http://www.gurobi.com/index>. CPLEX can be obtained from <https://www.ibm.com/analytics/cplex-optimizer>. CPLEX R APIs Rcplex and cplexAPI are available from CRAN. MOSEK and the MOSEK R API can be obtained from <https://www.mosek.com/>. The lp_solve library is freely available from <http://lpsolve.sourceforge.net/5.5/>, and is included when installing its API lpSolveAPI', which is available from CRAN.

Nonparametric estimation on survival analysis under order-restrictions.

Interactive shiny application for running Item Response Theory analysis. Provides graphics for characteristic and information curves.

This package contains datasets and several smaller functions suitable for analysis of interval-censored data. The package complements the book Bogaerts, Komárek and Lesaffre (2017, ISBN: 978-1-4200-7747-6) "Survival Analysis with Interval-Censored Data: A Practical Approach" <https://www.routledge.com/Survival-Analysis-with-Interval-Censored-Data-A-Practical-Approach-with/Bogaerts-Komarek-Lesaffre/p/book/9781420077476>. Full R code related to the examples presented in the book can be found at <https://ibiostat.be/online-resources/icbook/supplemental>. Packages mentioned in the "Suggests" section are used in those examples.

Drawing statistical inference on the coefficients of a short- or long-horizon predictive regression with persistent regressors by using the IVX method of Magdalinos and Phillips (2009) <doi:10.1017/S0266466608090154> and Kostakis, Magdalinos and Stamatogiannis (2015) <doi:10.1093/rfs/hhu139>.

Geostatistical interpolation has traditionally been done by manually fitting a variogram and then interpolating. Here, we introduce classes and methods that can do this interpolation automatically. Pebesma et al (2010) gives an overview of the methods behind and possible usage <doi:10.1016/j.cageo.2010.03.019>.

Estimation of reliability coefficients for ability estimates and sum scores from item response theory models as defined in Cheng, Y., Yuan, K.-H. and Liu, C. (2012) <doi:10.1177/0013164411407315> and Kim, S. and Feldt, L. S. (2010) <doi:10.1007/s12564-009-9062-8>. The package supports the 3-PL and generalized partial credit models and includes estimates of the standard errors of the reliability coefficient estimators, derived in Andersson, B. and Xin, T. (2018) <doi:10.1177/0013164417713570>.

This package provides a set of functions to estimate interactions flexibly in the face of possibly many controls. Implements the procedures described in Blackwell and Olson (2022) <doi:10.1017/pan.2021.19>.

Get open statistical data and metadata disseminated by the National Statistics Institute of Spain (INE). The functions return data frames with the requested information thanks to calls to the INE API <https://www.ine.es/dyngs/DAB/index.htm?cid=1100>.

This package provides user-friendly and configurable print debugging via a single function, ic(). Wrap an expression in ic() to print the expression, its value and (where available) its source location. Debugging output can be toggled globally without modifying code.

This package provides functions to perform robust nonparametric survival analysis with right censored data using a prior near-ignorant Dirichlet Process. Mangili, F., Benavoli, A., de Campos, C.P., Zaffalon, M. (2015) <doi:10.1002/bimj.201500062>.

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.

Generates Personality Insights sunburst diagrams based on IBM Watson Personality Insights service output.

It provides a general framework to analyse dependence between point processes in time. It includes parametric and non-parametric tests to study independence, and functions for generating and analysing different types of dependence.