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The sparsity and bias of the lasso selection in highdimensional linear regression. Ann. Statist. Volume 36, Number 4, 15671594. Alexandre Belloni Duke University Fuqua
 School of Business 1 Towerview Drive Durham, NC 277080120 PO Box 90120 Email: abn5@duke.edu Victor Chernozhukov Massachusetts Institute of Technology Department of Economics and Operations research Center 50 Memorial Drive Room E52262f Cambridge, MA 02
, 2008
"... showed that, for neighborhood selection in Gaussian graphical models, under a neighborhood stability condition, the LASSO is consistent, even when the number of variables is of greater order than the sample size. Zhao and Yu [(2006) J. Machine Learning Research 7 2541–2567] formalized the neighborho ..."
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Cited by 191 (27 self)
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for the mean response and the ℓαloss for the regression coefficients converge at the best possible rates under the given conditions. An interesting aspect of our results is that the logarithm of the number of variables can be of the same order as the sample size for certain random dependent designs. 1
Stochastic and Dependence Comparisons Between Extreme Order Statistics in the Case of Proportional Reversed Hazard Model
, 2011
"... Abstract. Independent random variables Y1,..., Yn belongs to the proportional reversed hazard rate (PRHR) model with proportionality parameters λ1,..., λn, if Yk ∼ Gλk(x), for k = 1,..., n, where G is an absolutely continuous distribution function. In this paper we compare the smallest order stat ..."
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statistics, the sample ranges and the ratios of the smallest and largest order statistics of two sets of independent random variables belonging to PRHR model, in the sense of (reversed) hazard rate order, likelihood ratio order and dispersive order, when the variables in one set have proportionality
Selfdetermination and persistence in a reallife setting: Toward a motivational model of high school dropout.
 Journal of Personality and Social Psychology,
, 1997
"... The purpose of this study was to propose and test a motivational model of high school dropout. The model posits that teachers, parents, and the school administration's behaviors toward students influence students' perceptions of competence and autonomy. The less autonomy supportive the so ..."
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Cited by 183 (19 self)
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covariance matrix of the observed variables (which also include the means) is shown in the Appendix. The model was statistically tested using L1SREL VII Structural and measurement coefficients from the completely standardized solution under maximum likelihood are displayed in The less autonomy supportive
6 Finite Sample Theory of Order Statistics and Extremes The
"... ordered values of a sample of observations are called the order statistics of the sample, and the smallest and the largest called the extremes. Order statistics and extremes are among the most important functions of a set of random variables that we study in probability and statistics. There is natu ..."
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ordered values of a sample of observations are called the order statistics of the sample, and the smallest and the largest called the extremes. Order statistics and extremes are among the most important functions of a set of random variables that we study in probability and statistics
Whom You Know Matters: Venture Capital Networks and Investment Performance,
 Journal of Finance
, 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm'slength, spotmarket transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
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Cited by 138 (8 self)
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as the dependent variable. Parametric hazard models require that we specify a distribution for log time. While our results are robust to alternative choices, we assume that log time is normally distributed. This has the advantage that the hazard rate (the instantaneous probability of exiting in the next instance
and Statistics
, 2006
"... We analyze the consumptionportfolio selection problem of an investor facing both Brownian and jump risks. By adopting a factor structure for the asset returns and decomposing the two types of risks on a well chosen basis, we provide a new methodology for determining the optimal solution up to an im ..."
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We analyze the consumptionportfolio selection problem of an investor facing both Brownian and jump risks. By adopting a factor structure for the asset returns and decomposing the two types of risks on a well chosen basis, we provide a new methodology for determining the optimal solution up to an implicitly defined constant, which in some cases can be reduced to a fully explicit closed form, irrespectively of the number of assets available to the investor. We show that the optimal policy is for the investor to focus on controlling his exposure to the jump risk, while exploiting differences in the asset returns diffusive characteristics in the orthogonal space. We also examine the solution to the portfolio problem as the number of assets increases and the impact of the jumps on the diversification of the optimal portfolio.
Causality Testing using Higher Order Statistics
"... Abstract: A new causality test based on Higher Order Statistics (HOS) is proposed in this paper. The test can be applied on non Gaussian time series. The methodological novelty is the usage of a two step causality test based on digital whitening, which is performed by ARMAHOS filters. To substanti ..."
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step applies ARMAHOS models to obtain white residuals from quarterly term structure (TS) and GDP growth. The second step tests dynamical correlation of TS and GDP growth residuals. Results show that the proposed test can capture the information about non Gaussian properties of the random variables
Multivariate analysis and Jacobi ensembles: Largest eigenvalue, Tracy–Widom limits and rates of convergence
 ANN. STATIST
, 2008
"... Let A and B be independent, central Wishart matrices in p variables with common covariance and having m and n degrees of freedom, respectively. The distribution of the largest eigenvalue of (A+B) −1 B has numerous applications in multivariate statistics, but is difficult to calculate exactly. Suppos ..."
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Cited by 30 (2 self)
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Let A and B be independent, central Wishart matrices in p variables with common covariance and having m and n degrees of freedom, respectively. The distribution of the largest eigenvalue of (A+B) −1 B has numerous applications in multivariate statistics, but is difficult to calculate exactly
The SpatialTemporal Statistics Of Rain Rate Random Fields
"... Rain rate near the ground can be interpreted as a collection of random variables forming a random field parameterised by three coordinates: two spatial coordinates and one temporal. Interest among the radio propagation community has been focused on the first order statistics of these random variab ..."
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Cited by 2 (1 self)
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Rain rate near the ground can be interpreted as a collection of random variables forming a random field parameterised by three coordinates: two spatial coordinates and one temporal. Interest among the radio propagation community has been focused on the first order statistics of these random
SecondOrder Regular Variation and Rates of Convergence in ExtremeValue Theory
 Ann. Probab
, 1995
"... Rates of convergence of the distribution of the extreme order statistic to its limit distribution are given in the uniform metric and the total variation metric. A secondorder regular variation condition is imposed by supposing a von Mises type condition which allows a unified treatment. Rates are ..."
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Cited by 9 (0 self)
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Rates of convergence of the distribution of the extreme order statistic to its limit distribution are given in the uniform metric and the total variation metric. A secondorder regular variation condition is imposed by supposing a von Mises type condition which allows a unified treatment. Rates
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