estimation/imputation
Imputation vs Estimation of Finite Population Distributions
... this imputation approach with direct estimation of the wage rate distribution using the derived wage rate variable as an ...two imputation approaches, one based on substituting the derived wage rate ...
25
A Comparative Study between Multiple Imputation Method and Regression Imputation Method of Estimation of Missing Data
... multiple imputation method was lower than the ...multiple imputation method which was also lower than MAE of regression imputation ...multiple Imputation method best than regression ...
10
Identity by descent estimation with population and pedigree based imputation in admixed family data
... based imputation, we used a set of 351 well-spaced SNPs (Marker Set 2 [MS-2]; Table 1) extracted from the SNP data of all genotyped individuals in these 16 ...
7
The accuracy of estimation procedures based on the imputation of plausible values
... (ML) estimation and Expected A Pos- teriori (EAP) ...two estimation procedures resulted out of respectively a frequentist and a Bayesian approach to ...parameter estimation procedure is in some way ...
51
Estimation of genotype imputation accuracy using reference populations with varying degrees of relationship and marker density panel
... markers imputation error rate reduced up to ...of imputation between France's dairy cattle resulted from using more markers due to the way of markers edi- tion and having denser ...that imputation ...
9
Mean Estimation under Imputation based on Two-Phase Sampling Design using an Auxiliary Variable
... The present article offers more efficient imputation based estimators of the population mean under the framework of two-phase sampling in presence of an auxiliary variable. The theoretical conditions stating ...
20
Statistical Analysis Of A Class: Monte Carlo And Multiple Imputation Spreadsheet Methods For Estimation And Extrapolation
... multiple imputation is that because it has multiple replacement values for each missing value, it allows you to calculate a confidence interval for each observation and for the class as a ...“multiple ...
16
HYBRID MODELS FOR EFFICIENT CALCULATION OF OMITTED VALUES
... Notice that for the likelihood-based hybrid the marginal improvement in accuracy does not de-crease monotonically with increasing model storage: the most frequent patterns are not necessarily the patterns that lead to ...
7
Application of imputation methods to genomic selection in Chinese Holstein cattle
... Genomic selection is becoming prevalent and practic- able in dairy cattle breeding, where genomic breeding values of animals are estimated using high density single nucleotide polymorphisms (SNPs) and are the basis for ...
5
Discrete measurement, continuous time and event history modeling
... parameter estimation under conditions of general interval-censoring are already well developed for both the Cox proportional hazard model and parametric ...midpoint imputation can bias results in the ...
37
Comparison of methods for imputing limited-range variables: a simulation study
... under- estimation of the between-imputation variance from the post-imputation rounding method, resulted in under- coverage, particularly for the standard GHQ with the se- vere ...normal ...
11
Stewart_unc_0153D_15589.pdf
... multiple imputation and provided conditions for the method’s appli- cation to unbiased estimation, also see Schafer [93], Harel and Zhou [46] and Rubin ...general imputation types: single and ...
174
On the Adjustment of Non-Response through Imputation for Estimating Current Mean in Repeated Surveys
... The estimates of population parameters obtained through one-time surveys are usually relevant only up to a limited period of time and could not be used for populations which is dynamic, in the sense that population ...
18
Shrinkage Estimation of Semiparametric Model with Missing Responses for Cluster Data
... Abstract This paper simultaneously investigates variable selection and imputation estimation of semiparametric partially linear varying-coefficient model in that case where there exist m[r] ...
9
Generating Tree Lists by Fusing Individual Tree Detection and Nearest Neighbor Imputation Using Airborne LiDAR Data
... SPH estimation might be data pits, which are height irregularities in a ...SPH estimation than no smoothing and the smoothing with a 3 by 3 ...SPH estimation at the finer ...
32
Using data augmentation to correct for nonignorable nonresponse when surrogate data are available: An application to the distribution of hourly pay
... the estimation of hourly pay distributions using UK Labour Force Survey (LFS) data provides the main ...deck imputation methods as part of the data augmentation procedure to improve the robustness of the ...
30
ISSN: 2321-8363 Impact Factor: 4.123
... data imputation and significance analysis of differential expression,” Bioinformatics, ...value estimation of epistatic miniarray profiling data by a novel ensemble approach,” Genomics, ...
7
Estimating the financial impact of data quality issues
... data imputation procedures work on a variable-by-variable ...data imputation procedures can also be used to cleanse datasets with other types of incorrect values than missing ...data imputation ...
79
Computational Techniques To Recover Missing Data From Gene Expression Data
... value imputation of other genes. In Gaussian mixture clustering imputation (GMCimpute), the data is clustered into S components Gaussian mixtures using the EM ...and estimation steps are iterated ...
10
Missing Categorical Data Imputation and Individual Observation Level Imputation
... 4 APPLICABILITY OF THE ALGORITHM The proposed method of estimation of missing data could be used in many spheres of application. In this paper we demonstrated the algorithm on (completely or partially unknown) ...
8