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Multivariate Granger Causality and Generalized Variance
Granger causality causal inference multivariate statistics generalized variance
2010/3/11
Granger causality analysis is a popular method for inference on directed interactions in complex systems of many variables. A shortcoming of the standard framework for Granger causality is
that it on...
A Multivariate Variance Components Model for Analysis of Covariance in Designed Experiments
Adjusted mean blocking factor conditionalmodel orthogonal design randomized blocks design.itute of Mathematical Statistics
2010/3/9
Traditional methods for covariate adjustment of treatment
means in designed experiments are inherently conditional on the ob-
served covariate values. In order to develop a coherent general method-
...
A functional limit theorem for partial sums of dependent random variables with infinite variance
convergence in distribution functional limit the-orem GARCH mixing moving average partial sum point processes reg-ular variation
2010/3/9
Under an appropriate regular variation condition, the affinely
normalized partial sums of a sequence of independent and identically dis-
tributed random variables converges weakly to a non-Gaussian ...
Unpacking Firm Effects: Modeling Political Alliances in Variance Decomposition of Firm Performance in Turbulent Environments
firm heterogeneity variance decomposition firm performance turbulent environments political strategies
2009/9/25
In this paper, firm heterogeneity in turbulent environments is addressed. It is argued that previous studies have not taken into account effects of a turbulent environment, like the Brazilian context,...
The Variance Composition of Firm Growth Rates
variance components growth competitive advantage
2009/9/25
Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this vari...
On minimum bias and variance estimation for parametric models with shrinking contamination
minimum bias and variance estimation parametric models shrinking contamination
2009/9/24
A close relationship is derived between optimal Mestimation
and optimal robust testing for shrinking contaminations.
Explicit formulas are given for solutions when the loss is defined as
convex com...
Estimating functions of variance components is
considered. The problem is to find an estimator, the variance of
which changes as little as possible when the kurtosis of the
underlying distribution ...
Admissibility of limits of the unique locally best linear estimators with application to variance components models
Admissibility of limits the unique locally best linear estimators
2009/9/23
The paper gives a sufkient condition for the limit of
a sequence of the unique best linear estimators to be admissible. For
commutative variance components models a complete characterization
of hrn...
Variance components admissible estimation from some unbalanced data: formulae for the nested design (1)
Variance components admissible estimation unbalanced data
2009/9/23
Variance components admissible estimation from some unbalanced data: formulae for the nested design (1)。
The minimal complete class for the vector of variance components
The minimal complete class the vector of variance components
2009/9/23
The minimal complete class for the vector of variance components。
Admissible estimators of variance components in normal mixed models
Admissible estimators variance components normal mixed models
2009/9/23
A sulficient condition for an invariant quadratic
estimator of a linear function of the vector of variance components to
be admissible under the mean square &or among all translation
invariant esti...
Stochastic processes with linear conditional expectation and quadratic conditional variance
Stochastic processes linear conditional expectation quadratic conditional variance
2009/9/23
Linear conditional expectations and quadratic conditional
variances determine a class of stochastic processes with
independent increments. Characterizations of the Wiener, Poisson,
gamma, negative ...
For a symmetric a-stable random vector (XI.,. . , X,,X ,+ ,)
with 1 < a < 2 and spectral measure r, we find a necessary and
sufficient condition in terms of r for the conditional variance
Var(X,+l ...
Prediction of infinite variance fractional ARIMA: 65
Prediction infinite variance fractional ARIMA: 65
2009/9/22
We establish conditions for the existence and invertibility
of fractionally differenced ARIMA time series whose innovations
are in the domain of attraction of an a-stable law with E < 2
and consequ...
M-estimation for linear regression with infinite variance
M-estimation linear regression infinite variance
2009/9/22
The limiting behavior of M-estimates for a Iinear model
when the regressors and/or errors have heavy tailed distributions is
given. By hermy toil we mean that the distribution is in the domain of
a...