How To Use Covariance In A Sentence
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The most common measure of variability is variance and the corresponding measure of correlation between two variables is covariance.
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An analysis of covariance was used to test whether differences between the slopes of regression lines were significant.
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To explore possible correlative effects among physiological and growth traits, we conducted two separate analyses of covariance, using the main effects of treatment and species.
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Covariance velocity spectrum is based on the fact that the sampled data can be arranged in eigen structure of covariance matrix.
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To compare the sites, plant age, A, was transformed as log to linearize the relationships, and log was used as the covariate in covariance analysis.
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We used analysis of covariance to test differences in the slopes among interday calibration curves.
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Finally to calculate the yield of the risky assets and the underwriting yield covariance, and to calculated effective portfolio will via inputting variable data into the insurance portfolio model.
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For the estimation of satellite state, the extended sequential estimation algorithm was applied. The numerical method was used to integrate state vector and error covariance matrix.
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Our approach in the 2002 paper was an analysis of covariance, with age and handedness (both of which had significant effects) as covariates.
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Variance component model of the random effects of covariance matrix unit for the "Linear model introduction" matrix has been studied.
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To check for robustness of results in this experimental study we used analysis of variance, analysis of covariance, and nested design.
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As such, although these points are presented in Fig.7, the data were omitted from analysis of covariance.
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The main problem for the latter is the general covariance of the field equations of General Relativity: any spacetime model and its image under a diffeomorphism (a infinitely differentiable, one-one and onto mapping of the model to itself) are in all observable respects equivalent to one another; all physical properties are expressed in terms of generally covariant relationships between geometrical objects.
Structural Realism
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If this occurs frequently, then MA experiments will be practically useless for studying any properties of mutational covariance.
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Now the covariance matrix can be written as where T is the transpose, U is an orthogonal matrix (, I is an identity matrix), D is a diagonal matrix matrix of eigenvalues (nonnegative numbers).
Reconciling Zorita « Climate Audit
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In a flexible variance-components framework, modeling such covariation as a covariance component in our analyses is straightforward.
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We then used the analysis of covariance to test for differences between the slopes of the regression lines for the eubacterial and the archaeal data sets.
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Some of the math is quite sophisticated, using differential equations, linear algebra, and covariance matrices.
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Logistic regression was used instead of univariate chi-squares so that covariance among the variables would be taken into account in the analyses.
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Note that the simulated covariance function was not generated from a polynomial.
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Goodness-of-fit values for covariance functions estimated from three different methods on simulated data
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The main problem for the latter is the general covariance of the field equations of General Relativity: any spacetime model and its image under a diffeomorphism (a infinitely differentiable, one-one and onto mapping of the model to itself) are in all observable respects equivalent to one another; all physical properties are expressed in terms of generally covariant relationships between geometrical objects.
Structural Realism
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Because the components must sum to unity, converting values to proportions produces a linear constraint, which causes the sample covariance matrix to be singular.
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Results of tests of outliers and assumptions of normality, homogeneity of variance-covariance matrices, linearity, and multicollinearity were satisfactory.
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Analysis of covariance revealed some relationships between subspecies morphology / growth habit and local environmental conditions.
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Realized covariance matrix is a new measurement of the volatility and correlation of portfolio.
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To control for differences in the age distribution, we analysed the logarithmic transformed variables using analysis of covariance, in which we included age as a continuous covariate.
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The demographic variances and covariances of the elements are inversely proportional to the total population size.
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Previous work has calculated the covariance expected under autosomal inheritance in diploids and haploids.
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The direct estimation approach does well in estimating the overall covariance function: on average, the covariances are estimated with an error of 15%.
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The matrix formulation of the model produces an estimate that can be easily transformed into genetic covariance and correlations.
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It shows that the genetic variances and covariances contributed by the additive and dominance effects cannot be fully controlled in the model.
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With covariance matching technique and innovation information of filtering, the noise variance is dynamically adjusted and the mean square error of the fusion system always keeps minimum.
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Statistical inference The regression model Estimating the model The OLS estimator Hypothesis testing The variance of the OLS estimator When the assumptions break down Background reading The variance-covariance matrix of β ˆ We'll generally want to ask questions about single coef fi cients in the model-e. g, is β2 different from zero?
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The residual covariance matrix of the share equations will be singular, and thus one equation must be omitted when estimating the system.
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Methods Scale was used to assess the QOL of children, body mass index (BMI) was used to classify the children. Analysis of covariance was used to compare the QOL among different groups.
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One-way analysis of covariance, with pretest scores as covariants, were used when tests for homogeneity of variance dictated that ANCOVA was warranted.
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These different models for covariance function with some modifications can be incorporated into our mapping strategy.
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The technique is intended to integrate Mendelian transmission genetics, allelic frequency, and penetrance with the patterns of covariance expected in polygenic inheritance.
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A novel DOA estimation algorithm based on the largest eigenvalue of the covariance matrix is presented. It mainly applies to the pencil beam smart antenna in DS CDMA systems.
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A separate analysis of covariance was calculated on each dependent variable.
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Modeling and Generating Multivariate Time Series with Arbitrary Marginals Using a Vector Autoregressive Technique by Deler and Nelson wherein is an equation for covariance of VAR(1) process , for zero-lag where is autoregressive coefficient matrix and and is covariance matrix of driving noise (white in time).
Bürger Review « Climate Audit
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Compared with the traditional method, it does not need disassembling the power spectral densities of stochastic signal covariance and is not bound to if the power spectral densities are rational.
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Contour plots of genetic covariance functions fitted by the character process model.
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Variance component model of the random effects of covariance matrix unit for the "Linear model introduction" matrix has been studied.
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The plots show that residues lining the gorge have the largest velocity covariance with the gorge, and residues in the same moiety as the gorge move concertedly away from the gorge when it opens.
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Statistically significant covariances among random intercepts, rates of change, and effects of depressed mood and delinquency variety are reported in the text only.
