In statistics, inverse-variance weighting is a method of aggregating(聚集) two or more random variables to minimize the variance of the sum. Each random variable in the sum is weighted in inverse proportion to its variance. Given a sequence of observations yi with independent variances σi2, t...
Applying MRlap to obesity-related exposures revealed statistically significant differences between IVW-based and corrected effects, both for nonoverlapping and fully overlapping samples. Our method not only reduces bias in causal effect estimation but also enables the use of much larger GWAS samp...
A robust ratio estimator of gene expression via inverse-variance weighting for cDNA microarray images. Computational Statistics & Data Analysis 53 (5), 1577-1589.Shih-Huang Chan , Wan-Chi Chang, A robust ratio estimator of gene expression via inverse-variance weighting for cDNA microarray images,...
In addition, for low SNR, the RIM had lower variance than the ResNet, suggesting that the neighborhood context alone is not the sole responsible for the increased quality, and that the data consistency term (likelihood function) in the RIM framework helps to produce more reliable estimates. ...
We performed fixed-effect meta-analysis based on inverse-variance weighting for HUNT, MGI, and ThyroidOmics in METAL61. Cochran’sQ-test62for heterogeneity has been conducted using METAL61. We performed genomic control correction prior to and after the meta-analysis. We identified LD-independent ge...
Suppose R is the variance-covariance matrix when a Gaussian noise component is assumed and Y is the matrix corresponding to the measurements y. The R-norm is defined as follows: ||Y−KX||R2=Tr[(Y−KX)TR−1(Y−KX)] MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MD...
Suppose R is the variance-covariance matrix when a Gaussian noise component is assumed and Y is the matrix corresponding to the measurements y. The R-norm is defined as follows: | | Y − K X | | R 2 = T r [ ( Y − K X ) T R − 1 ( Y − K X ) ] MathType@MTEF...
In larger samples IPTW using the propensity score method may however be a useful alternative. Williamson et al. demonstrated the large sample equivalence between the IPTW-W variance estimator and the analysis of covariance variance estimator theoretically and via simulation. Our simulation results ...
Define Cycles as the total number of the commands, then: ∑Cycles Et = ||θ˙ ||(51) i=1 Em = C Et ycles (52) Method SNS LP_Basic Performance Total time [s] Mean(e) [mm] Variance(e) Cycles Total time [s] Mean(e) [mm] Variance(e) Cycles TAB = 1 s / / / Stop ...
k i=0 λs,i p i=0 λs,i >T and k i=0 λt,i p i=0 λt,i > T, (8) where T is a threshold controlling the proportion of ex- plained variance by the first k principal components. In the following, the pseudo-inverse with respect ...