Variance partitioning estimates (%) using two methods
Detection of changes in variance using binary segmentation and optimal partitioning
... The results for the first time-series are quite good as all changepoints are detected by both meth- ods. However, each method detects one changepoint where the parameter stays constant. For the sec- ond time-series ...
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Yield Estimates by a Two-Step Approach Using Hyperspectral Methods in Grasslands at High Latitudes
... multivariate methods such as partial least squares (PLS) [8] or machine learning algorithms [9]; the last two are generally preferred over MLR due to their robustness against collinearity ...[14]. ...
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Variance of wind estimates using spaced antenna techniques with the MU radar
... The variance of wind estimates is related to CCF magni- ...the two sets of baselines with the greatest (and equal) align- ment to this orientation, (B 12 , B 23 ) and (B 13 , B 23 ), show the lowest ...
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Estimates of Variance Components for Gilt Retention Traits.
... retention. Methods of boar exposure to insure maximum effectiveness of estrous detection have been studied (Hemsworth et ...estrus using the back-pressure test was less efficient when gilts were housed with ...
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Comparison of Variance Estimates in a National Health Survey
... 2 National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD 20782 Abstract The National Health Interview Survey (NHIS) is one of the major data collection ...
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A comparison of two methods for detecting abrupt changes in the variance of climatic time series
... the two methods was first implemented using Monte Carlo simulations with series of 100 points, which is a typical length (in years) of instrumental climatic time ...the variance increases from ...
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Comparing Time-Use Estimates of Two Different Time Diary Methods
... selected using multistage stratified cluster sampling method in ...analyzed using Kolmogorov-Smirnov Test, Pearson correlation coefficient, Spearman correlation coefficient, 2-way ANOVA, Independent t-test ...
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Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
... gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, ...the variance of the performance ...
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Measuring the Stability of Recursive Partitioning Methods
... Measuring Stability Recursive Partitioning Stability of Trees Stability Framework Framework Parts Using the Framework Use Cases R package stablelearner Summary Stability Framework I Two [r] ...
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Comparison of variance estimators for meta-analysis of instrumental variable estimates
... models, using for example a Firth 27,28 or Lasso 29 penalization, are expected to perform ...between-study variance or ...and variance estimates will influence the observed heterogeneity, ...
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Comparison of variance estimators for meta-analysis of instrumental variable estimates.
... models, using for example a Firth(27;28) or Lasso(29) penalization, are expected to perform ...study variance or ...and variance estimates will influence the observed heterogeneity, resulting ...
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Search for the Optimum Variance Components Estimates in Mixed Effects Models
... Minimum Variance (MINVAR) quadratic estimators 20 , the Minimum Mean Square (MIMS) quadratic estimators 16 ...estimation methods are the Maximum Likelihood (ML) estimation methods (9 (), 10 ()), and ...
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Integrating methods for determining length-at-age to improve growth estimates for two large scombrids
... by using ANOVA and ...provide estimates of growth parameters that are more appro- priate representations of the population (Ballagh et ...different methods for determining ...
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Markowitz Minimum Variance Portfolio Optimization using New Machine Learning Methods
... A new approach of discovering the pattern of zeros in the inverse covariance matrix by formulating a convex relaxation to the problem was proposed by [30]. The authors derive two first-order algorithms for solving ...
287
A General Unified Framework to Assess the Sampling Variance of Heritability Estimates Using Pedigree or Marker-Based Relationships
... estimated using identity-by-descent calculations con- ditional on observed marker ...the variance of realized relationships, see Hill and Weir ...sampling variance of the estimate of heritability ...
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Comparison of Estimates on Two Occasions Involving Stratification using Successive Sampling
... population estimates from one occasion to another using double sampling ...estimate using double sampling approach with ...population estimates of two occasions involving stratification ...
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Cache-oblivious sparse matrix-vector multiplication by using sparse matrix partitioning methods
... established methods, we also run experiments using OSKI (optimized sparse kernel interface) [39] on the original matrix as well as on reordered versions ...matrix using two different SpMV ...
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Assessing Complex Genetic Effects Using Variance Component Based Marker-set Methods.
... with two major challenges: (1) how to better account for the within-gene multi-marker information[53, 54]; (2) how to appropriately assess association at both gene set level and gene level [61, ...the two ...
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Methods for evaluating value-at-risk estimates
... VaR estimates generated by banks’ own VaR models using the standardizing parameters of a ten-day holding period and 99 percent coverage ...subsequent two- week ...sixty estimates, that ...
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Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato
... genetic variance partitioning in tetraploids with covariance matrices constructed from genome-wide allele dosage ...a two-stage analysis in which the genotype estimate for each clone 3 environment ...
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