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Managing Audits to Manage Earnings: Th Impact of Baiting Tactics on an Auditor’s Ability to Uncover Earnings Management Errors
Managing Audits Manage Earnings Baiting Tactics on an Auditor’s Ability Earnings Management Errors
2014/10/28
This study examines an aspect of earnings management that I refer to as audit management. I define audit management as a client’s strategic use of techniques (e.g., baiting tactics) to prevent auditor...
Adaptive estimation in nonparametric regression with one-sided errors
adaptive convergence rates non-regular regression frontier estimation bandwidth selection Lepski's method minimax optimality Pickands estimator
2013/6/14
We consider the model of non-regular nonparametric regression where smoothness constraints are imposed on the regression function and the regression errors are assumed to decay with some sharpness lev...
Reducing decision errors in the paired comparison of the diagnostic accuracy of screening tests with Gaussian outcomes
cancer screening differential verification bias area under the curve type I error power paired screening trial receiver operating characteristic analysis
2013/6/14
Scientists often use a paired comparison of the areas under the receiver operating characteristic curves to decide which continuous cancer screening test has the best diagnostic accuracy. In the paire...
Universal Approximation Depth and Errors of Narrow Belief Networks with Discrete Units
Deep belief network restricted Boltzmann machine universal approxima-tion representational power Kullback-Leibler divergence,q-ary variable
2013/4/28
We generalize recent theoretical work on the minimal number of layers of narrow deep belief networks that can approximate any probability distribution on the states of their visible units arbitrarily ...
Propagation of initial errors on the parameters for linear and Gaussian state space models
Kalman filter Extended Kalman filter State space mod-els Autoregressive process
2013/4/27
For linear and Gaussian state space models parametrized by $\theta_0 \in \Theta \subset \R^{r}, r \geq 1$ corresponding to the vector of parameters of the model, the Kalman filter gives exactly the so...
Unified Analysis of Transmit Antenna Selection/Space-Time Block Coding with Receive Selection and Combining over Nakagami-m Fading Channels in the Presence of Feedback Errors
Space-Time Block Coding (STBC) Transmit Antenna Selection (TAS) Receive Antenna Selection (RAS) Maximal-ratio Combining (MRC) Selection Combining (SC) Nakagami-m fading Feedback Errors
2012/9/18
Examining the effect of imperfect transmit antenna selection (TAS) caused by the feedback link errors on the performance of hybrid TAS/space-time block co ding (STBC) with selection combining (SC) (i....
Wavelet Deconvolution in a Periodic Setting with Long-Range Dependent Errors
Besov Spaces Deconvolution fractional Brownian motion Long-Range Dependence Maxiset theory Wavelet Analysis
2012/9/17
In this paper, a hard thresholding wavelet estimator is constructed for a deconvolution model in a periodic setting that has long-range dependent noise. The estimation paradigm is based on a maxiset m...
Bayesian semi-parametric forecasting with penalised splines and autoregressive errors
splines, autoregressive errors, semi-parametric regression, Bayesian
2012/9/18
Observational time series data often exhibit both cyclic temporal trends and autocorrelation and may also depend on covariates. As such, there is a need for exible regression models that are able to c...
Scaling of Model Approximation Errors and Expected Entropy Distances
Scaling of Model Approximation Errors Expected Entropy Distances
2012/9/19
We compute the expected value of the Kullback-Leibler divergence to various fundamental statistical models with respect to canonical priors on the probability simplex. This yields information about th...
Scaling of Model Approximation Errors and Expected Entropy Distances
Scaling of Model Approximation Errors Expected Entropy Distances
2012/9/19
We compute the expected value of the Kullback-Leibler divergence to various fundamental statistical models with respect to canonical priors on the probability simplex. This yields information about th...
Some results on random design regression with long memory errors and predictors
memory errors predictors random design
2011/3/24
This paper studies nonparametric regression with long memory (LRD) errors and predictors. First, we formulate general conditions which guarantee the standard rate of convergence for a nonparametric ke...
Empirical process of residuals for regression models with long memory errors
Empirical process of residuals regression models
2011/3/24
We consider the residual empirical process in random design regression with long memory errors. We establish its limiting behaviour, showing that its rates of convergence are different from the rates ...
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors
Adaptive nonparametric estimation Deconvolution Fluorescence lifetimes
2010/11/8
Motivated by fluorescence lifetime measurements this paper considers the problem of nonparametric density estimation in the pile-up model. Adaptive nonparametric estimators are proposed for the pile-u...
Nonparametric kernel estimation of the probability density function of regression errors using estimated residuals
Kernel density estimation Leave-one-out kernel estimator Two-steps estimator
2010/10/14
This paper deals with the nonparametric density estimation of the regression error term assuming its independence with the covariate. The difference between the feasible estimator which uses the estim...
Kink estimation in stochastic regression with dependent errors and predictors
Change point Kink High-order kernel Zero-crossing technique Long-range dependence Random Design Separationrate lemma
2010/3/11
In this article we study the estimation of the location of jump
points in the first derivative (referred to as kinks) of a regression function
μ in two random design models with different long-range...