항목
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Principal component regressionPLS) estimator. Similar to PCR, PLS also uses derived covariates of lower dimensions. However unlike PCR, the derived covariates for PLS are obtained based on using both the outcome as well as the covariates. While PCR seeks the high variance directions in the space of the covariates, PLS seeks...출처 영어 위키백과
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Hájek–Le Cam convolution theoremell(\theta) is the score function, and ′ denotes matrix transpose. Theorem . Suppose Tn is a uniformly (locally) regular estimator of the parameter q. Then There exist independent random m-vectors \scriptstyle Z_\theta\,\sim\,\mathcal{N}(0,\,I^{-1}_{q(\theta)}) and Δθ such that where d denotes...출처 영어 위키백과
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Allan variancebetween measurements is denoted with T, which is the sum of observation time τ and dead-time. Fixed τ estimators A first simple estimator would be to directly translate the definition into \sigma_y^2(\tau, M) = \text{AVAR}(\tau, M) = \frac{1}{2(M-1)} \sum_{i=0}^{M-2}(\bar{y}_{i+1}-\bar{y}_i)^2...출처 영어 위키백과
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Average absolute deviationrobust estimator of dispersion.For the example {2, 2, 3, 4, 14}: 3 is the median, so the absolute deviations from the median are {1, 1, 0, 1, 11} (reordered as {0, 1, 1, 1, 11}) with a median of 1, in this case unaffected by the value of the outlier 14, so the median absolute deviation (also...출처 영어 위키백과
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Weighted arithmetic meanour estimator we need to pre-divide by 1 - \left(V_2 / V_1^2\right) , ensuring that the expected value of the estimated variance equals the actual variance of the sampling distribution.The final unbiased estimate of sample variance is: \begin{align} s^2\ &= \frac{\hat \sigma^2_\mathrm{weighted...출처 영어 위키백과
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Epigenetic clockage estimator was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. The major innovation of Horvath's epigenetic clock lies in its wide applicability: the same set of 353 CpGs and the same prediction algorithm is used...출처 영어 위키백과
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Optimal designunbiased estimator of a predetermined linear combination of model parameters. D-optimality (determinant) A popular criterion is D-optimality, which seeks to minimize |(X'X)−1|, or equivalently maximize the determinant of the information matrix X'X of the design. This criterion results in...출처 영어 위키백과
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Multivariate kernel density estimationcross validation and plug-in selectors. The plug-in (PI) estimate of the AMISE is formed by replacing Ψ4 by its estimator \hat{\bold{\Psi}}_4 \operatorname{PI}(\bold{H}) = n^{-1} |\bold{H}|^{-1/2} R(K) + \tfrac{1}{4} m_2(K)^2 (\operatorname{vec}^T \bold{H}) \hat{\bold{\Psi}}_4 (\bold{G...출처 영어 위키백과
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Minimum mean square erroror cannot be found. Let x be a n \times 1 hidden random vector variable, and let y be a m \times 1 known random vector variable (the measurement or observation), both of them not necessarily of the same dimension. An estimator \hat{x}(y) of x is any function of the measurement y. The estimation...출처 영어 위키백과
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Zero-inflated modelestimators are given by \hat{\lambda}_{mo} = \frac{s^2+m^2-m}{m}, \hat{\pi}_{mo} = \frac{s^2 - m}{s^2 + m^2 - m}, where m is the sample mean and s^2 is the sample variance.The maximum likelihood estimator can be found by solving the following equation \bar{x}(1- e^{-\hat{\lambda}_{ml}}) = \hat...출처 영어 위키백과
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Effect size 效应值unbiased estimator is \hat{\sigma}^2(g^*) = \frac{n_1+n_2}{n_1 n_2} + \frac{(g^*)^2}{2(n_1 + n_2)}. \phi = \sqrt{ \frac{\chi^2}{N}} \phi_c = \sqrt{ \frac{\chi^2}{N(k - 1)}} Phi (φ) Cramér's V (φc) Commonly used measures of association for the chi-squared test are the Phi coefficient and...출처 영어 위키백과
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Simultaneous equations modelend{bmatrix} Several estimators belong to this class: κ=0: OLS κ=1: 2SLS. Note indeed that in this case, I-\kappa M = I-M= P the usual projection matrix of the 2SLS κ=λ: LIML κ=λ - α (n-K): estimator. Here K represents the number of instruments, n the sample size, and α a positive...출처 영어 위키백과