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matlab's statistical tool box  (MathWorks Inc)


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    MathWorks Inc matlab's statistical tool box
    Matlab's Statistical Tool Box, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 25 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/statistical+tool+box/MATLAB+Production+Server+Client+Libraries/pmc06929626-187-28-32
    Average 93 stars, based on 25 article reviews
    matlab's statistical tool box - by Bioz Stars, 2026-11
    93/100 stars

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    Related Articles

    Modification:

    Article Title: Exploiting Online Spatially Resolved Dynamic Light Scattering and Flow-NMR for Automated Size Targeting of PISA-Synthesized Block Copolymer Nanoparticles
    Article Snippet: .. The instrument’s proprietary flow correction algorithms decoupled flow motion from diffusive motion in the phase resolved signal to yield final autocorrelation functions at each pathlength in Figure S9.1–3 A modified cumulants fitting method was used to obtain the cumulants Z-Average hydrodynamic diameter (d.nm) and a polydispersity index (PDI) for the expected monomodal distribution.4 A MATLAB™ Client interfaced with the instrument using the Open Platform Communications Unified Protocol (OPCUA) for real-time monitoring, data collection and instrument control over a network connection. ..

    Control:

    Article Title: Exploiting Online Spatially Resolved Dynamic Light Scattering and Flow-NMR for Automated Size Targeting of PISA-Synthesized Block Copolymer Nanoparticles
    Article Snippet: .. The instrument’s proprietary flow correction algorithms decoupled flow motion from diffusive motion in the phase resolved signal to yield final autocorrelation functions at each pathlength in Figure S9.1–3 A modified cumulants fitting method was used to obtain the cumulants Z-Average hydrodynamic diameter (d.nm) and a polydispersity index (PDI) for the expected monomodal distribution.4 A MATLAB™ Client interfaced with the instrument using the Open Platform Communications Unified Protocol (OPCUA) for real-time monitoring, data collection and instrument control over a network connection. ..

    other:

    Article Title: Teacups, a Python Package for the Simulation of Time-Resolved EPR Spectra of Spin-Polarized Multi-Spin Systems.
    Article Snippet: A XXXX, XXX, XXX−XXX L (39) Pribitzer, S.; Doll, A.; Jeschke, G. SPIDYAN, a MATLAB library for simulating pulse EPR experiments with arbitrary waveform excitation.

    Article Title: Comparative Study of Machine Learning and System Identification for Process Systems Engineering Dynamics
    Article Snippet: All data-driven models were implemented using a mixture of Python and MATLAB libraries/toolboxes.

    Article Title: The Fourier–Malliavin Volatility (FMVol) MATLAB® library
    Article Snippet: To describe our MATLAB® library, e generate a single trajectory of a bi-variate version of the well-known stochastic volatility model by [13]: dx1(t) = ( μ1 − 1 2 v1(t) ) dt + √ v1(t)dW 1t (23) dx2(t) = ( μ2 − 1 2 v2(t) ) dt + √ v2(t)dW 2t (24) dv1(t) = θ1(α1 − v1(t))dt + γ1 √ v1(t)dW 3t (25) dv2(t) = θ2(α2 − v2(t))dt + γ2 √ v2(t)dW 4t (26) where W 1,W 2,W 3,W 4 are correlated Brownian motions such that ⟨dW kt , dW rt ⟩ = ρk,r dt.

    Transmission Assay:

    Article Title: Process simulation and evaluation of scaled-up biocatalytic systems: Advances, challenges, and future prospects.
    Article Snippet: With the increased demand for bio-based products and the rapid development of biomanufacturing technologies, biocatalytic reactions including microorganisms and enzyme based, have become promising approaches.. Prior to the scale-up of production process, environmental and economic feasibility analysis are essential for the development of a sustainable and intelligent bioeconomy in the context of industry 4.0.. To achieve these goals, process simulation supports system optimization, improves energy and resource utilization efficiencies, and supports digital bioprocessing.



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    Image Search Results


    Voltage U—RMSE: D-PNN = 1.153, SMLT (Tree) = 1.118 [V], 12 inputs + THDU (both D-PNN and SMLT) in the 2nd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Voltage U—RMSE: D-PNN = 1.153, SMLT (Tree) = 1.118 [V], 12 inputs + THDU (both D-PNN and SMLT) in the 2nd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power P—RMSE: D-PNN = 0.177, SMLT (GPR) = 0.182 [kW], 12 inputs + U + PF (D-PNN), 12 inputs + PF + THDU (SMLT) in the 3rd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power P—RMSE: D-PNN = 0.177, SMLT (GPR) = 0.182 [kW], 12 inputs + U + PF (D-PNN), 12 inputs + PF + THDU (SMLT) in the 3rd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    THDU—RMSE: D-PNN = 0.429, SMLT (Tree) = 0.443 [%], 12 inputs + U (both D-PNN and SMLT) in the 2nd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: THDU—RMSE: D-PNN = 0.429, SMLT (Tree) = 0.443 [%], 12 inputs + U (both D-PNN and SMLT) in the 2nd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power Factor PF—RMSE: D-PNN = 0.0516, SMLT (GPR) = 0.0496 [], 12 inputs + Pst + U (D-PNN, 12 inputs + Pst + THDU (SMLT) in the 3rd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power Factor PF—RMSE: D-PNN = 0.0516, SMLT (GPR) = 0.0496 [], 12 inputs + Pst + U (D-PNN, 12 inputs + Pst + THDU (SMLT) in the 3rd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Pst—RMSE: D-PNN = 0.811, SMLT (EBoosT) = 0.544 [], 12 inputs + Pst (both D-PNN and SMLT) in the 2nd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Pst—RMSE: D-PNN = 0.811, SMLT (EBoosT) = 0.544 [], 12 inputs + Pst (both D-PNN and SMLT) in the 2nd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Voltage U 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Voltage U 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power P 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power P 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    THDU 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: THDU 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power Factor PF 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power Factor PF 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Pst 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Pst 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques: