Variance Estimation
On generalized variance of normal Poisson model and Poisson variance estimation under Gaussianity
... generalize variance estimators of normal- Poisson models have been introduced (see ...by variance function and by generalized variance of normal-Poisson have been successfully proven (see ...Poisson ...
7
Variance estimation for a low income proportion
... their variance estimator with some re-sampling methods, including the jackknife, the bootstrap and balanced half ...inconsistent variance estimation in the case of quantiles and Kovaˇ cevi´c and Yung ...
21
Superpixel-based image noise variance estimation with local statistical assessment
... noise estimation algorithm, which computes the noise variance by convolving the image with a Laplacian-like mask with zero ...the variance of noise and showed the effectiveness on images with ...
12
Variance Estimation for High Dimensional Varying Index Coefficient Models
... the variance estimation in the case of high-dimensional ...the variance estimated by this method is stable and ...the variance estimation of linear models under certain as- ...residual ...
16
Second order accurate variance estimation in poststratified two-stage sampling
... Poststratified estimation of population total is one of popular methods in point esti- mation used in survey ...the variance estimation, previous research has adopted two prin- cipal approaches, ...
86
Noise Variance Estimation To Detect Forgery In Digital Images
... noise variance estimation with the use of ...noise variance estimation of each block of the segmented image, an unsupervised clustering algorithm is used to divide blocks into groups depending ...
6
Bootstrap algorithms for variance estimation in complex survey sampling
... A BSTRACT . The problem of estimating the variance of the Horvitz-Thompson estimator under a prob- ability proportional to size design is concerned. Some IPPS-bootstrap algorithms are proposed with the purpose of ...
6
Automatic variance control and variance estimation loops
... of variance is required if a Least-Mean Squares (LMS) algorithm is used for weight vector estimation ...the variance recursively. That is, (assuming large k) for a sample variance σ k 2 of k ...
12
Non-linear minimum variance estimation for fault detection systems
... Minimum Variance ( NMV) estimation technique is used to generate a residual signal which is then used to detect actuator and sensor faults in the ...
17
A comparison of block and semi-parametric bootstrap methods for variance estimation in spatial statistics
... Table 2: True values of σ12 and approximates of the NBias, NVar and NMSE for MBB and SPB estimators σ ˆ12 based on exponential covariogram.. Table 3: True values of σ12 and approximates [r] ...
35
A note on the asymptotic equivalence of jackknife and linearization variance estimation for the Gini coefficient
... The jackknife is a numerical method which can be used to estimate a variance (Miller 1974). In particular, the jackknife technique is commonly employed to estimate the variance of the Gini coefficient ...
15
Variance estimation for measures of change in probability sampling
... design variance of absolute changes between two cross- sectional estimators under rotating sampling ...the variance estimator proposed is generally ...
21
A. Bootstrap and Jackknife Variance Estimation
... variable to be imputed increases the proportion of missing data in that variable. This affects the results of the imputation process, since more values need to be imputed. Further, since the method deletes values ...
9
Bayesian Nonparametric Estimation of Ex post Variance
... Variance estimation is central to many questions in finance and ...ex-post variance estimation has been based on infill asymptotic assumptions that exploit high-frequency ...ex-post ...
49
Variance Function Estimation in Multivariate Nonparametric Regression
... function estimation in multivariate nonparametric regression is considered and the minimax rate of convergence is established in the iid Gaussian ...based variance estimation in nonparametric ...
21
Methods of variance component estimation
... Before we discuss some of the existing methods of estimation, let us make a general remark. In (1) the model equation of the random variables y is given. Its realisations as well as the data observed are de- noted ...
9
Variance targeting estimation of multivariate GARCH models
... We establish the strong consistency and the asymptotic normality of the variance-targeting es- timator (VTE) of the parameters of the multivariate CCC-GARCH(p, q) processes. This method alleviates the numerical ...
36
Estimation of finite population variance using auxiliary information in sample surveys
... population variance using auxiliary information in sample ...population variance have been suggested along with their properties in simple random ...
18
Maximum likelihood estimation of variance components
... estimating variance components: they are all variations on ANOVA estimates which involve equating various quadratic forms of the observations to their expected values, then solving for the variance ...
76
Further Bounds for the Estimation Error Variance of a Continuous Stream with Stationary Variogram
... The paper [1] was concerned with issues related to sampling the stream with a view to estimating the mean quality characteristic of the flow, ¯ X, over the interval [0, d] . Specifically, focus was on obtaining the ...
6