Metabolomics data was log10 transformed (with pseudo count 1 for zero values) and tested for significance in R with linear mixed-effect models correcting for subject using the lmer function from the lmerTest package with formula lmer(data ∼cohort + (1|subject_id). Comparison contrasts were ex...
As earlier stated, the multicollinearity influences the performance of the maximum likelihood estimator (MLE) in both the linear regression models and the Poisson regression models (PRM). The ridge regression and Liu estimator at a different time were harmonized to the PRM to solve multicollinearity....
The magnitude of NSE is computed using the formula below: $$NSE=1-\frac{\sum_{i=1}^{n}{\left({X}_{oi}-{X}_{mi}\right)}^{2}}{\sum_{i=1}^{n}{\left({X}_{oi}-{\overline{X}}_{mi}\right)}^{2}}$$ (1) The magnitude of R2 is calculated using the following equati...
Binomial logistic regression assumes alogistic distributionof the data, where the probability that an example belongs to class 1 is the formula: p(x;β0,…, βD-1) Where: x is a D-dimensional vector containing the values of all the features of the instance. ...
is defined as a Boolean function by the following formula: CI,E(YN1,YN2)=E(I(YN1),I(YN2))where for all YN∈Ω, I(YN)=(I1(YN),I2(YN),…,Ik(YN)).If every Ii for i=1,2,…,k is binary, the comparison method CI,E(YN1,YN2) is defined as a Boolean function by ...
Create a rocmetrics object to evaluate the performance of a classification model using receiver operating characteristic (ROC) curves or other performance metrics.
The formula syntax is very similar to that of the package lme4 to provide a familiar and simple interface for performing regression analyses. A wide range of response distributions are supported, allowing users to fit – among others – linear, robust linear, count data, survival, response ...
We may estimate Sharpley value of the above model in a computationally efficient way by Deep SHAP35 with the following recursive formula: $${\phi }_{q,r}\left({f}^{\left(l-1\right)}\circ {f}^{\left(l\right)}{,\,{{{\bf{e}}}^{\left(l-1\right)}\right)=\left({{{e}}...
8b), and we used a UoSS linear regression model to fit all components to tissue MSI data while forcing model weights to be non-negative (Methods). The weights could then be interpreted as the cell-type-specific contributions and yielded deconvolved cellular features at every tissue pixel (Fig...
(seehttps://mc-stan.org/). The formula syntax is very similar to that of the package lme4 to provide a familiar and simple interface for performing regression analyses. A wide range of response distributions are supported, allowing users to fit – among others – linear, robust linear, ...