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fHMM - Fitting Hidden Markov Models to Financial Data

Fitting (hierarchical) hidden Markov models to financial data via maximum likelihood estimation. See Oelschläger, L. and Adam, T. "Detecting Bearish and Bullish Markets in Financial Time Series Using Hierarchical Hidden Markov Models" (2021, Statistical Modelling) <doi:10.1177/1471082X211034048> for a reference on the method. A user guide is provided by the accompanying software paper "fHMM: Hidden Markov Models for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R. (2024, Journal of Statistical Software) <doi:10.18637/jss.v109.i09>.

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financehidden-markov-modelscppopenmp

6.41 score 23 stars 14 scripts 629 downloads

RprobitB - Bayesian Probit Choice Modeling

Fits Bayesian probit models for binary, multinomial, ordered, and ranked choices in cross-sectional and panel data. Correlated or uncorrelated normal and log-normal random coefficients, finite mixtures, sparse finite mixtures, and Dirichlet process mixtures describe preference heterogeneity. Multiple Gibbs chains produce posterior draws for diagnostics and choice prediction. Choice data can be supplied as a data frame or simulated from the requested specification. For an overarching treatment of the methodology, see Oelschlaeger (2026) <https://pub.uni-bielefeld.de/record/3014719>. The latent-class model is described in Oelschlaeger and Bauer (2021) <https://trid.trb.org/view/1759753>.

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bayesdiscrete-choicemcmc-samplerprobitopenblascppopenmp

6.37 score 6 stars 26 scripts 750 downloads

oeli - Some Utilities for Developing Data Science Software

A collection of general-purpose helper functions that I (and maybe others) find useful when developing data science software. Includes tools for simulation, data transformation, input validation, and more.

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openblascppopenmp

5.20 score 2 stars 8 dependents 4 scripts 1.1k downloads

ao - Alternating Optimization

Implementation of an iterative process that optimizes a function by alternately performing restricted optimization over parameter subsets. Instead of solving one joint optimization problem, alternating optimization breaks it into smaller sub-problems. This approach can make optimization feasible when joint optimization is too difficult.

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optimization

4.65 score 3 stars 6 scripts 651 downloads

optimizeR - Unified Framework for Numerical Optimizers

Provides a unified object-oriented framework for numerical optimizers in R. Supports minimization and maximization with any optimizer, optimization over more than one function argument, computation time measurement, and time limits for long optimization tasks.

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optimization

4.57 score 5 stars 5 dependents 6 scripts 734 downloads

ino - Initialization of Numerical Optimization

Analysis of the initialization for numerical optimization of real-valued functions, particularly likelihood functions of statistical models. See <https://loelschlaeger.de/ino/> for more details.

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optimization

4.30 score 2 stars 1 scripts 303 downloads

choicedata - Working with Choice Data

Offers a set of objects tailored to simplify working with choice data. It enables the computation of choice probabilities and the likelihood of various types of choice models based on given data.

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openblascpp

4.02 score 1 stars 1 dependents 1 scripts 844 downloads

vntrs - Variable Neighborhood Trust Region Search

Implements a variable neighborhood trust region search (VNTRS) algorithm for nonlinear global optimization, based on Bierlaire et al. (2009) "A Heuristic for Nonlinear Global Optimization" <doi:10.1287/ijoc.1090.0343>. The method combines neighborhood exploration with a trust-region framework to search the solution space efficiently. It can terminate a local search early when the iterates converge toward a previously visited local optimum or when further improvement within the current region is unlikely. The algorithm can also be used to identify multiple local optima.

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openblascppopenmp

3.18 score 3 scripts 317 downloads

normalize - Centering and Scaling of Numeric Data

Provides simple methods for centering and scaling of numeric data. Columns or rows can be ignored when normalizing or be normalized jointly.

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3.18 score 1 dependents 8 scripts 307 downloads

portion - Extracting a Data Portion

Provides simple methods to extract data portions from various objects. The relative portion size and the way the portion is selected can be chosen.

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3.18 score 1 dependents 2 scripts 246 downloads

trackopt - Track Numerical Optimization

Tracks parameter values, gradients, and Hessians at each iteration of numerical optimizers. Useful for analyzing optimization progress, diagnosing issues, and studying convergence behavior.

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optimization

2.70 score 1 scripts 290 downloads