robust local regression rlowess routine Search Results


rlowess  (MathWorks Inc)
90
MathWorks Inc rlowess
Cerebrospinal fluid (CSF) biomarker trajectories. The graphs represent the z‐scores changes of each CSF biomarker using the mean and the standard deviation of that CSF biomarker in the A–T– group as a reference. The resulting z‐scores are shown as a function of CSF Aβ42/40 (A) p‐tau (B) or p‐tau/Aβ42 (C) using a robust <t>local</t> <t>weighted</t> <t>regression</t> <t>method.</t> The solid lines depict the trajectory of each CSF biomarker. The dashed lines depict the cutoff for CSF Aβ42/40, p‐tau, and p‐tau/Aβ42, respectively. The horizontal axis direction of CSF Aβ42/40 (A) was inverted.
Rlowess, 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
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Average 90 stars, based on 1 article reviews
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lowess local regression matlab 'smooth' function  (MathWorks Inc)
90
MathWorks Inc lowess local regression matlab 'smooth' function
Cerebrospinal fluid (CSF) biomarker trajectories. The graphs represent the z‐scores changes of each CSF biomarker using the mean and the standard deviation of that CSF biomarker in the A–T– group as a reference. The resulting z‐scores are shown as a function of CSF Aβ42/40 (A) p‐tau (B) or p‐tau/Aβ42 (C) using a robust <t>local</t> <t>weighted</t> <t>regression</t> <t>method.</t> The solid lines depict the trajectory of each CSF biomarker. The dashed lines depict the cutoff for CSF Aβ42/40, p‐tau, and p‐tau/Aβ42, respectively. The horizontal axis direction of CSF Aβ42/40 (A) was inverted.
Lowess Local Regression Matlab 'smooth' Function, 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/lowess local regression matlab 'smooth' function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
lowess local regression matlab 'smooth' function - by Bioz Stars, 2026-03
90/100 stars
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robust locally weighted scatterplot smoothing (rlowess) filter  (MathWorks Inc)
90
MathWorks Inc robust locally weighted scatterplot smoothing (rlowess) filter
Cerebrospinal fluid (CSF) biomarker trajectories. The graphs represent the z‐scores changes of each CSF biomarker using the mean and the standard deviation of that CSF biomarker in the A–T– group as a reference. The resulting z‐scores are shown as a function of CSF Aβ42/40 (A) p‐tau (B) or p‐tau/Aβ42 (C) using a robust <t>local</t> <t>weighted</t> <t>regression</t> <t>method.</t> The solid lines depict the trajectory of each CSF biomarker. The dashed lines depict the cutoff for CSF Aβ42/40, p‐tau, and p‐tau/Aβ42, respectively. The horizontal axis direction of CSF Aβ42/40 (A) was inverted.
Robust Locally Weighted Scatterplot Smoothing (Rlowess) Filter, 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/robust locally weighted scatterplot smoothing (rlowess) filter/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
robust locally weighted scatterplot smoothing (rlowess) filter - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier
matlab function "smooth  (MathWorks Inc)
90
MathWorks Inc matlab function "smooth
Cerebrospinal fluid (CSF) biomarker trajectories. The graphs represent the z‐scores changes of each CSF biomarker using the mean and the standard deviation of that CSF biomarker in the A–T– group as a reference. The resulting z‐scores are shown as a function of CSF Aβ42/40 (A) p‐tau (B) or p‐tau/Aβ42 (C) using a robust <t>local</t> <t>weighted</t> <t>regression</t> <t>method.</t> The solid lines depict the trajectory of each CSF biomarker. The dashed lines depict the cutoff for CSF Aβ42/40, p‐tau, and p‐tau/Aβ42, respectively. The horizontal axis direction of CSF Aβ42/40 (A) was inverted.
Matlab Function "Smooth, 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 function "smooth/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab function "smooth - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

Image Search Results


Cerebrospinal fluid (CSF) biomarker trajectories. The graphs represent the z‐scores changes of each CSF biomarker using the mean and the standard deviation of that CSF biomarker in the A–T– group as a reference. The resulting z‐scores are shown as a function of CSF Aβ42/40 (A) p‐tau (B) or p‐tau/Aβ42 (C) using a robust local weighted regression method. The solid lines depict the trajectory of each CSF biomarker. The dashed lines depict the cutoff for CSF Aβ42/40, p‐tau, and p‐tau/Aβ42, respectively. The horizontal axis direction of CSF Aβ42/40 (A) was inverted.

Journal: Alzheimer's & Dementia

Article Title: Amyloid beta, tau, synaptic, neurodegeneration, and glial biomarkers in the preclinical stage of the Alzheimer's continuum

doi: 10.1002/alz.12131

Figure Lengend Snippet: Cerebrospinal fluid (CSF) biomarker trajectories. The graphs represent the z‐scores changes of each CSF biomarker using the mean and the standard deviation of that CSF biomarker in the A–T– group as a reference. The resulting z‐scores are shown as a function of CSF Aβ42/40 (A) p‐tau (B) or p‐tau/Aβ42 (C) using a robust local weighted regression method. The solid lines depict the trajectory of each CSF biomarker. The dashed lines depict the cutoff for CSF Aβ42/40, p‐tau, and p‐tau/Aβ42, respectively. The horizontal axis direction of CSF Aβ42/40 (A) was inverted.

Article Snippet: The relationship between each CSF biomarker and the proxies of disease progression (ie, CSF Aβ42/40, p‐tau, and p‐tau/Aβ42) were modelled using a robust local weighted regression method (rlowess; “smooth” function in Matlab and a span of 300) and we plotted the resulting model. , Moreover, we calculated the linear regression slopes for each of the biomarkers in each of the negative or positive groups, using the previously described cutoffs.

Techniques: Biomarker Discovery, Standard Deviation