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maximum likelihood estimator function mle  (MathWorks Inc)


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    MathWorks Inc maximum likelihood estimator function mle
    Maximum Likelihood Estimator Function Mle, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/maximum+likelihood+estimation+(mle)+function/pmc08824488-351-34-29
    Average 90 stars, based on 1 article reviews
    maximum likelihood estimator function mle - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Drug-resilient Cancer Cell Phenotype Is Acquired via Polyploidization Associated with Early Stress Response Coupled to HIF2α Transcriptional Regulation
    Article Snippet: To explore whether the sample could come from a truncated normal distribution, we used the “mle” function of MATLAB with the option “TruncationBounds”.

    Article Title: Cerebellar control of a unitary head direction sense
    Article Snippet: The fitted functions were optimized using the “mle” 290 function in MATLAB and custom-made code adopted from the codes available online (22).

    Article Title: Stepwise disassembly of GABAergic synapses during pathogenic excitotoxicity
    Article Snippet: A high throughput pipeline for analysis is as follows: synapses were processed by background subtraction (ImageJ), image segmentation (split-Bregman/MOSAIC suite ( ; )) and geometric analysis (MATLAB) as further detailed in .

    Article Title: Single-Molecule Diffusivity Quantification Unveils Ubiquitous Net Charge-Driven Protein-Protein Interaction.
    Article Snippet: 1) Here a = 4DΔt with D being the diffusion coefficient, and b accounts for a uniform background due to extraneous molecules that randomly diffuse into the search radius during Δt.4 MLE with MATLAB returned 95% confidence intervals for a, which were then converted to D using the fixed Δt (600 μs) in the experiment.

    Article Title: Droplet size distribution, atomization mechanism and dynamics of dental aerosols
    Article Snippet: The parameters of the probability density functions (pdfs) were obtained by MATLAB Statistics and Machine Learning ToolboxTM function ‘mle’ by fitting droplet size data to bimodal lognormal pdfs.

    Article Title: Bound2Learn: a machine learning approach for classification of DNA-bound proteins from single-molecule tracking experiments
    Article Snippet: We fit the track durations of the resulting tracks with a truncated exponential model, to compensate for discarding short duration tracks, using maximum likelihood estimation (MLE) through Matlab's ‘mle’ function, to calculate the mean track duration.

    Article Title: Comparative analysis of joint distribution models for tropical cyclone atmospheric parameters in probabilistic coastal hazard analysis
    Article Snippet: In probabilistic coastal hazard assessments based on the Joint Probability Method, historical storm data is used to build distribution models of tropical cyclone atmospheric parameters (i.e., central pressure deficit, forward velocity, radius of maximum wind, and heading direction).. Recent models have used a range of assumptions regarding the dependence structure between these random variables.. This research investigates the performance of a series of joint distribution models based on assumptions of parameter independence, partial-dependence (i.e., dependence between only central pressure deficit and radius of maximum wind), and full dependence (i.e., dependence between each pair of tropical cyclone atmospheric parameters).

    Article Title: Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions
    Article Snippet: As discussed in , the use of MLE in MATLAB for the alpha-stable distribution depends on the choice of initial values to start the optimization routine.



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