https://hzambran.github.io/tags/time-series/ Time Series HugoBlox Kit (https://hugoblox.com)en-usThu, 15 Jan 2026 00:00:00 +0000 https://hzambran.github.io/media/icon_hu_edd58fc588fafe6f.png https://hzambran.github.io/tags/time-series/ https://hzambran.github.io/rpackages/hydromopso/ Thu, 15 Jan 2026 00:00:00 +0000 https://hzambran.github.io/rpackages/hydromopso/ <style> /* 1. Target the main article container broadly */ body .page-body, body .universal-wrapper, article.article { font-size: 1rem !important; /* Forces base size to 16px */ } /* 2. Target paragraphs and lists specifically with !important */ .article-style p, .article-container p, article p, .project-content p { font-size: 1rem !important; line-height: 1.6 !important; } /* 3. Target list items */ .article-style li, .article-container li, article li { font-size: 1rem !important; } </style> <!-- Fotos --> <figure><img src="https://hzambran.github.io/rpackages/hydromopso/hydroMOPSO-logo.jpg" alt="hydroMOPSO R package."><figcaption> <p>R package.</p> </figcaption> </figure> <h2 id="description">Description</h2> <p> is an R package designed to support robust multi-objective optimisation of complex environmental and engineering models. It implements a state-of-the-art <strong>Multi-Objective Particle Swarm Optimisation (MOPSO)</strong> algorithm, tailored to address the practical challenges commonly encountered in hydrological modelling, such as non-linearity, non-smooth response surfaces, computationally intensive simulations, and competing performance criteria.</p> <p> is built to integrate seamlessly with real-world modelling workflows. It can optimise models written in R as well as external simulation models executed from the system console—such as distributed hydrological or water quality models—by communicating through standard input and output files. This architecture allows users to perform advanced optimisation without modifying model source code, preserving model integrity while enabling systematic calibration across multiple parameters, variables, and time periods.</p> <p>It was designed by <strong>Rodrigo Marinao</strong> and I to be flexible and computational efficienct. supports parallel execution on multi-core machines and computing clusters, making it suitable for large-scale calibration and decision-support applications. Its configurable optimisation settings and multi-objective capabilities enable users to explore trade-offs among performance metrics and identify parameter sets that balance competing modelling goals.</p> <p> is widely applicable to hydrology and other environmental sciences, providing a technically rigorous and operationally practical framework for global optimisation. It is particularly well suited for researchers and practitioners who require transparent, reproducible, and scalable tools to calibrate complex models and support evidence-based analysis.</p> https://hzambran.github.io/rpackages/hydrotsm/ Mon, 11 Oct 2010 00:00:00 +0000 https://hzambran.github.io/rpackages/hydrotsm/ <style> /* 1. Target the main article container broadly */ body .page-body, body .universal-wrapper, article.article { font-size: 1rem !important; /* Forces base size to 16px */ } /* 2. Target paragraphs and lists specifically with !important */ .article-style p, .article-container p, article p, .project-content p { font-size: 1rem !important; line-height: 1.6 !important; } /* 3. Target list items */ .article-style li, .article-container li, article li { font-size: 1rem !important; } </style> <h2 id="description">Description</h2> <p> is an R package designed to support the practical workflow of hydrologists and environmental scientists who routinely work with time series data. It provides a comprehensive and coherent set of tools for the management, quality control, analysis, interpolation, and visualization of hydrological and environmental time series, with particular emphasis on tasks commonly encountered in hydrological modelling and water resources assessment.</p> <p> prioritises reliability, transparency, and functional breadth, reflecting the operational realities of applied hydrology, where reproducible data handling and robust diagnostics are often more critical than marginal computational gains. Its functions are built to integrate naturally into analytical pipelines, facilitating consistent preprocessing and exploration of observational datasets prior to modelling or decision-making.</p> <p>Developed with the daily needs of practitioners in mind, has been widely used in research, teaching, and professional applications. It is especially suitable for users who require dependable, well-documented tools to support routine hydrological analysis while maintaining full control over data processing steps within the R environment.</p> <!-- Fotos --> <figure><img src="https://hzambran.github.io/rpackages/hydrotsm/hydroTSM-logo.jpg" alt="hydroTSM R package."><figcaption> <p>R package.</p> </figcaption> </figure>