Search Results for "transfer function model"
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Showing 27 open source projects for "transfer function model"
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Mixed-effects models in Julia
A Julia package for fitting (statistical) mixed-effects models
This package defines linear mixed models (LinearMixedModel) and generalized linear mixed models (GeneralizedLinearMixedModel). Users can use the abstraction for statistical model API to build, fit (fit/fit!), and query the fitted models. A mixed-effects model is a statistical model for a response variable as a function of one or more covariates. For a categorical covariate the coefficients associated with the levels of the covariate are sometimes called effects, as in "the effect of using Treatment 1 versus the placebo". ... -
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Bayesian Statistics
This repository holds slides and code for a full Bayesian statistics
This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. -
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Surrogates.jl
Surrogate modeling and optimization for scientific machine learning
A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. -
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UMAP.jl
Uniform Manifold Approximation and Projection (UMAP) implementation
A pure Julia implementation of the Uniform Manifold Approximation and Projection dimension reduction algorithm. The umap function takes two arguments, X (a column-major matrix of shape (n_features, n_samples)), n_components (the number of dimensions in the output embedding), and various keyword arguments. -
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JuliaConnectoR
A functionally oriented interface for calling Julia from R
This R-package provides a functionally oriented interface between R and Julia. The goal is to call functions from Julia packages directly as R functions. Julia functions imported via the JuliaConnectoR can accept and return R variables. It is also possible to pass R functions as arguments in place of Julia functions, which allows callbacks from Julia to R. From a technical perspective, R data structures are serialized with an optimized custom streaming format, sent to a (local) Julia TCP... -
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Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal... -
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Lithops
A multi-cloud framework for big data analytics
Lithops is an open-source serverless computing framework that enables transparent execution of Python functions across multiple cloud providers and on-prem infrastructure. It abstracts cloud providers like IBM Cloud, AWS, Azure, and Google Cloud into a unified interface and turns your Python functions into scalable, event-driven workloads. Lithops is ideal for data processing, ML inference, and embarrassingly parallel workloads, giving you the power of FaaS (Function-as-a-Service) without... -
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DynamicHMC
Implementation of robust dynamic Hamiltonian Monte Carlo methods
Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent of coding a (log) posterior density in Julia. ... -
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Benthos
Fancy stream processing made operationally mundane
...It comes with a powerful mapping language, is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary, docker image, or serverless function, making it cloud native as heck. Delivery guarantees can be a dodgy subject. Benthos processes and acknowledges messages using an in-process transaction model with no need for any disk persisted state, so when connecting to at-least-once sources and sinks it's able to guarantee at-least-once delivery even in the event of crashes, disk corruption, or other unexpected server faults. ... -
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Inventory Forms
Inventory Forms
Inventory Transfer Forms and Case Management System. This system is designed to create and collect inventory's transfer documents. The created and printed document can be passed to a customer with the inventory as a transfer form. The system has an advanced search function useful to find a specific document by various fields. The second function is the service requests' management system. -
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Data Envelopment Analysis using Stata
Unified Data Envelopment Analysis commands for Stata
DEAS provides Data Envelopment Analysis tools for Stata. Version 2.0 is a major update centered on a unified dea command for Stata 16 or later. It consolidates sixteen DEA model families into one interface, keeps backward compatibility with the original inputs = outputs syntax, and adds a fast Mata two-phase revised simplex engine alongside Stata's LinearProgram() IPM engine. The package supports radial technical efficiency (CCR/BCC), SBM, additive model, radial and SBM super-efficiency, multiplier form, directional distance function, cost, revenue, profit, allocative efficiency, FDH, imprecise DEA, undesirable outputs, SBM with undesirable outputs, and congestion analysis. ... -
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rechne.exe
Command-line calculator and libray.
Easy-to-use command-line calculator for basic and scientific calculations. -
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JobScheduler
JobScheduler workload automation to execute jobs and workflows
JS7 JobScheduler runs executables, scripts and database procedures and can be operated with e.g. MySQL, PostgreSQL, SQL Server, Oracle databases. JS7 JobScheduler provides workflow patterns such as sequential and parallel task execution, forking, synchronization, cross-platform scheduling, job load sharing, fail-over and a real REST API. JS7 includes the components: * JOC Cockpit (user interface for inventory management and control) * Controller (orchestration of Agents) * Agents:... -
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Bayesian Julia
Bayesian Statistics using Julia and Turing
Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from classical inferential statistics that prohibits probability statements about parameters and is based on asymptotically sampling infinite samples from a theoretical population and finding parameter values that maximize the likelihood function. ... -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series... -
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employear
Employee attendance management with import and reports
Keep track of the attendances of employees. Use this grid per month to fill the daycode for the employees with the efficient data entry 'column fill'. Or use the import function (adapt it to your needs) to interprete data from an existing time tracking app to daycodes. Look for missing data, complete illness-, holidays etc. Compare the sum of the worked time with the todo-working time over the days by looking at the +/- saldo. Transfer the saldo to next month, or subtract the payed overtime. Look at employee/month/year views. ... -
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GeoJAGS
JAGS module with covariance functions and the CAR model.
A module for JAGS containing several covariance functions for point-referenced data analysis and a function that creates the precision matrix for the proper CAR model for areal data analysis. -
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Bias is a cross-platform versatile information management application / Organizer
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Roomba
A Node.js tool to examine the correctness of Open Data Metadata
Linked Open Data (LOD) has emerged as one of the largest collection of interlinked datasets on the web. Benefiting from this mine of data requires the existence of descriptive information about each dataset in the accompanying metadata. Such meta information is currently very limited to few data portals where they are usually provided manually thus giving little or bad quality insights. To address this issue, we propose a scalable automatic approach for extracting, validating and generating... -
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Hibersap
A Java library to communicate with SAP
Hibersap helps developers of Java applications to call business logic in SAP backends. It defines a set of Java annotations to map SAP function modules to Java classes as well as a small, clean API to execute these function modules and handle transaction and security aspects. Hibersap's programming model is quite similar to those of modern O/R mappers, significantly speeding up the development of SAP interfaces and making it much more fun to write the integration code. ... -
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SCOREMATH
Excel function for multi-criteria selection problems
SCOREMATH implements the simple-yet-ingenious weighted linear model for multi-criteria selection problems described in Ng, Wan Lung. "An efficient and simple model for multiple criteria supplier selection problem." European Journal of Operational Research 186, no. 3 (2008): 1059-1067. "There are many real situations where the decision makers are able to tell the criteria importance ranking (although they cannot tell the exact values of weights). The decision makers may not have enough... -
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Inotifyfs is a set of scripts, primarily on bash to allow user keep remote and local folders synced in real time in efficient way based on inotify kernel evens and function in user space.
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Firefly UML
A free, easy-to-use and user-friendly Java-based UML editor.
...For example, you can import your existing Java project into Firefly and generate nice-looking class diagrams within a matter of minutes. You can also go the other way around and export your model as skeleton Java code. -
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MTF Calculator calculates the Modulation Transfer Function (MTF) of an edge image stored in DICOM format and allows the contents to be copied to the clipboard or saved to a Comma-Separated Values (CSV) file.
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This software can simulate heat transfer in solid heterogenous materia using cellular automata. There are two different simulation methods and several test model implemented at the moment. It is also possible to define boundary conditions.
