matlab fitting package Search Results


glmnet for matlab (2013)  (MathWorks Inc)
90
MathWorks Inc glmnet for matlab (2013)
Glmnet For Matlab (2013), 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/result/glmnet for matlab (2013)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
glmnet for matlab (2013) - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
package autoregressive fit (arfit)  (MathWorks Inc)
90
MathWorks Inc package autoregressive fit (arfit)
Package Autoregressive Fit (Arfit), 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/result/package autoregressive fit (arfit)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
package autoregressive fit (arfit) - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
matlab package lsqnonlin  (MathWorks Inc)
90
MathWorks Inc matlab package lsqnonlin
Matlab Package Lsqnonlin, 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/result/matlab package lsqnonlin/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab package lsqnonlin - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
gamfit  (MathWorks Inc)
90
MathWorks Inc gamfit
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Gamfit, 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/result/gamfit/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
gamfit - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
nonlinear curve fitting package  (MathWorks Inc)
90
MathWorks Inc nonlinear curve fitting package
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Nonlinear Curve Fitting Package, 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/result/nonlinear curve fitting package/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
nonlinear curve fitting package - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
matlab 2020a package  (MathWorks Inc)
90
MathWorks Inc matlab 2020a package
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Matlab 2020a Package, 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/result/matlab 2020a package/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab 2020a package - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
curve fitting package  (MathWorks Inc)
90
MathWorks Inc curve fitting package
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Curve Fitting Package, 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/result/curve fitting package/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
curve fitting package - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
mathematical software package  (MathWorks Inc)
90
MathWorks Inc mathematical software package
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Mathematical Software Package, 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/result/mathematical software package/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
mathematical software package - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
r2017b fitlme package  (MathWorks Inc)
90
MathWorks Inc r2017b fitlme package
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
R2017b Fitlme Package, 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/result/r2017b fitlme package/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
r2017b fitlme package - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
autoregressive fit (arfit)  (MathWorks Inc)
90
MathWorks Inc autoregressive fit (arfit)
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Autoregressive Fit (Arfit), 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/result/autoregressive fit (arfit)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
autoregressive fit (arfit) - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
function 'fminsearch  (MathWorks Inc)
90
MathWorks Inc function 'fminsearch
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
Function 'fminsearch, 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/result/function 'fminsearch/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
function 'fminsearch - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier
r2016a software package  (MathWorks Inc)
90
MathWorks Inc r2016a software package
State classification of iEEG recordings using a <t>four-state</t> <t>HMM.</t> ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a <t>gamma</t> function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.
R2016a Software Package, 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/result/r2016a software package/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
r2016a software package - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

Image Search Results


State classification of iEEG recordings using a four-state HMM. ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a gamma function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.

Journal: Brain Communications

Article Title: Delta-gamma phase-amplitude coupling as a biomarker of postictal generalized EEG suppression

doi: 10.1093/braincomms/fcaa182

Figure Lengend Snippet: State classification of iEEG recordings using a four-state HMM. ( A ) State classification of an example iEEG trace from Patient 2 (reference electrode—FCz), where S2 is a seizure-like state, and S3 is PGES-like state. ( B ) Comparison of HMM-driven S3 state classification to the visually estimated PGES durations, with the overall correlation of 0.77 ( P = 0.009). ( C ) Histogram of S2 durations, with a gamma function fitted to the data. The shape parameter of the gamma function—alpha—was calculated to be 3.54 (95% CI 1.59–7.89), which is consistent with the average alpha for seizure duration distributions from Suffczynski et al. (2006) of 3.03 and from Bauer et al. (2017) of 2.66. ( D ) Histogram of S3 durations, with gamma function fitted to the data with alpha parameter calculated to be 2.21 (95% CI 1.01–4.82) which is consistent with alpha for PGES duration distributions from Bauer et al. (2017) of 1.54. This can also be compared to alpha value of 1.83 (95% CI 1.04–3.20) obtained from distribution of visually estimated PGES durations (not shown). These shape parameters suggest that the transitions (to and from seizure states) occur not according to Poisson process, but rather that the probability of transition varies with time. For both sections ( C ) and ( D ), n = 11.

Article Snippet: HMM-derived ictal and postictal state duration distributions were also fitted using a gamma function ( gamfit in the MATLAB package): (8) y = λ α x α - 1 e - λ x Γ ( α ) , where α is the shape parameter and λ is the rate parameter.

Techniques: Comparison