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1.
Time series arising in practice often have an inherently irregular sampling structure or missing values, that can arise for
example due to a faulty measuring device or complex time-dependent nature. Spectral decomposition of time series is a traditionally
useful tool for data variability analysis. However, existing methods for spectral estimation often assume a regularly-sampled
time series, or require modifications to cope with irregular or ‘gappy’ data. Additionally, many techniques also assume that
the time series are stationary, which in the majority of cases is demonstrably not appropriate. This article addresses the
topic of spectral estimation of a non-stationary time series sampled with missing data. The time series is modelled as a locally
stationary wavelet process in the sense introduced by Nason et al. (J. R. Stat. Soc. B 62(2):271–292, 2000) and its realization is assumed to feature missing observations. Our work proposes an estimator (the periodogram) for the
process wavelet spectrum, which copes with the missing data whilst relaxing the strong assumption of stationarity. At the
centre of our construction are second generation wavelets built by means of the lifting scheme (Sweldens, Wavelet Applications
in Signal and Image Processing III, Proc. SPIE, vol. 2569, pp. 68–79, 1995), designed to cope with irregular data. We investigate the theoretical properties of our proposed periodogram, and show that
it can be smoothed to produce a bias-corrected spectral estimate by adopting a penalized least squares criterion. We demonstrate
our method with real data and simulated examples. 相似文献
2.
The subject of the present study is to analyze how accurately an elaborated price jump detection methodology by Barndorff-Nielsen
and Shephard (J. Financ. Econom. 2:1–37, 2004a; 4:1–30, 2006) applies to financial time series characterized by less frequent trading. In this context, it is of primary interest to understand
the impact of infrequent trading on two test statistics, applicable to disentangle contributions from price jumps to realized
variance. In a simulation study, evidence is found that infrequent trading induces a sizable distortion of the test statistics
towards overrejection. A new empirical investigation using high frequency information of the most heavily traded electricity
forward contract of the Nord Pool Energy Exchange corroborates the evidence of the simulation. In line with the theory, a
“zero-return-adjusted estimation” is introduced to reduce the bias in the test statistics, both illustrated in the simulation
study and empirical case. 相似文献
3.
Shen PS 《Lifetime data analysis》2012,18(1):1-18
The cumulative incidence function provides intuitive summary information about competing risks data. Via a mixture decomposition
of this function, Chang and Wang (Statist. Sinca 19:391–408, 2009) study how covariates affect the cumulative incidence probability of a particular failure type at a chosen time point. Without
specifying the corresponding failure time distribution, they proposed two estimators and derived their large sample properties.
The first estimator utilized the technique of weighting to adjust for the censoring bias, and can be considered as an extension
of Fine’s method (J R Stat Soc Ser B 61: 817–830, 1999). The second used imputation and extends the idea of Wang (J R Stat Soc Ser B 65: 921–935, 2003) from a nonparametric setting to the current regression framework. In this article, when covariates take only discrete values,
we extend both approaches of Chang and Wang (Statist Sinca 19:391–408, 2009) by allowing left truncation. Large sample properties of the proposed estimators are derived, and their finite sample performance
is investigated through a simulation study. We also apply our methods to heart transplant survival data. 相似文献
4.
This paper considers the problem of hypothesis testing in a simple panel data regression model with random individual effects
and serially correlated disturbances. Following Baltagi et al. (Econom. J. 11:554–572, 2008), we allow for the possibility of non-stationarity in the regressor and/or the disturbance term. While Baltagi et al. (Econom.
J. 11:554–572, 2008) focus on the asymptotic properties and distributions of the standard panel data estimators, this paper focuses on testing
of hypotheses in this setting. One important finding is that unlike the time-series case, one does not necessarily need to
rely on the “super-efficient” type AR estimator by Perron and Yabu (J. Econom. 151:56–69, 2009) to make an inference in the panel data. In fact, we show that the simple t-ratio always converges to the standard normal distribution, regardless of whether the disturbances and/or the regressor are
stationary. 相似文献
5.
In this paper we present a unified discussion of different approaches to the identification of smoothing spline analysis of
variance (ANOVA) models: (i) the “classical” approach (in the line of Wahba in Spline Models for Observational Data, 1990; Gu in Smoothing Spline ANOVA Models, 2002; Storlie et al. in Stat. Sin., 2011) and (ii) the State-Dependent Regression (SDR) approach of Young in Nonlinear Dynamics and Statistics (2001). The latter is a nonparametric approach which is very similar to smoothing splines and kernel regression methods, but based
on recursive filtering and smoothing estimation (the Kalman filter combined with fixed interval smoothing). We will show that
SDR can be effectively combined with the “classical” approach to obtain a more accurate and efficient estimation of smoothing
spline ANOVA models to be applied for emulation purposes. We will also show that such an approach can compare favorably with
kriging. 相似文献
6.
Efficiency improvement in a class of survival models through model-free covariate incorporation 总被引:1,自引:1,他引:0
In randomized clinical trials, we are often concerned with comparing two-sample survival data. Although the log-rank test
is usually suitable for this purpose, it may result in substantial power loss when the two groups have nonproportional hazards.
In a more general class of survival models of Yang and Prentice (Biometrika 92:1–17, 2005), which includes the log-rank test as a special case, we improve model efficiency by incorporating auxiliary covariates that
are correlated with the survival times. In a model-free form, we augment the estimating equation with auxiliary covariates,
and establish the efficiency improvement using the semiparametric theories in Zhang et al. (Biometrics 64:707–715, 2008) and Lu and Tsiatis (Biometrics, 95:674–679, 2008). Under minimal assumptions, our approach produces an unbiased, asymptotically normal estimator with additional efficiency
gain. Simulation studies and an application to a leukemia study show the satisfactory performance of the proposed method. 相似文献
7.
A partially adaptive estimator for the censored regression model based on a mixture of normal distributions 总被引:1,自引:0,他引:1
Steven B. Caudill 《Statistical Methods and Applications》2012,21(2):121-137
The goal of this paper is to introduce a partially adaptive estimator for the censored regression model based on an error
structure described by a mixture of two normal distributions. The model we introduce is easily estimated by maximum likelihood
using an EM algorithm adapted from the work of Bartolucci and Scaccia (Comput Stat Data Anal 48:821–834, 2005). A Monte Carlo study is conducted to compare the small sample properties of this estimator to the performance of some common
alternative estimators of censored regression models including the usual tobit model, the CLAD estimator of Powell (J Econom
25:303–325, 1984), and the STLS estimator of Powell (Econometrica 54:1435–1460, 1986). In terms of RMSE, our partially adaptive estimator performed well. The partially adaptive estimator is applied to data
on wife’s hours worked from Mroz (1987). In this application we find support for the partially adaptive estimator over the usual tobit model. 相似文献
8.
This paper proposes a new probabilistic classification algorithm using a Markov random field approach. The joint distribution
of class labels is explicitly modelled using the distances between feature vectors. Intuitively, a class label should depend
more on class labels which are closer in the feature space, than those which are further away. Our approach builds on previous
work by Holmes and Adams (J. R. Stat. Soc. Ser. B 64:295–306, 2002; Biometrika 90:99–112, 2003) and Cucala et al. (J. Am. Stat. Assoc. 104:263–273, 2009). Our work shares many of the advantages of these approaches in providing a probabilistic basis for the statistical inference.
In comparison to previous work, we present a more efficient computational algorithm to overcome the intractability of the
Markov random field model. The results of our algorithm are encouraging in comparison to the k-nearest neighbour algorithm. 相似文献
9.
This note is on two theorems in a paper by Rainer Dyckerhoff (Allg. Stat. Arch. 88:163–190, 2004). We state a missing condition in Theorem 3. On the other hand, Theorem 2 can be weakened. 相似文献
10.
We develop a Bayesian analysis for the class of Birnbaum–Saunders nonlinear regression models introduced by Lemonte and Cordeiro
(Comput Stat Data Anal 53:4441–4452, 2009). This regression model, which is based on the Birnbaum–Saunders distribution (Birnbaum and Saunders in J Appl Probab 6:319–327,
1969a), has been used successfully to model fatigue failure times. We have considered a Bayesian analysis under a normal-gamma
prior. Due to the complexity of the model, Markov chain Monte Carlo methods are used to develop a Bayesian procedure for the
considered model. We describe tools for model determination, which include the conditional predictive ordinate, the logarithm
of the pseudo-marginal likelihood and the pseudo-Bayes factor. Additionally, case deletion influence diagnostics is developed
for the joint posterior distribution based on the Kullback–Leibler divergence. Two empirical applications are considered in
order to illustrate the developed procedures. 相似文献
11.
The analysis of time-indexed categorical data is important in many fields, e.g., in telecommunication network monitoring,
manufacturing process control, ecology, etc. Primary interest is in detecting and measuring serial associations and dependencies
in such data. For cardinal time series analysis, autocorrelation is a convenient and informative measure of serial association.
Yet, for categorical time series analysis an analogous convenient measure and corresponding concepts of weak stationarity
have not been provided. For two categorical variables, several ways of measuring association have been suggested. This paper
reviews such measures and investigates their properties in a serial context. We discuss concepts of weak stationarity of a
categorical time series, in particular of stationarity in association measures. Serial association and weak stationarity are
studied in the class of discrete ARMA processes introduced by Jacobs and Lewis (J. Time Ser. Anal. 4(1):19–36, 1983).
An intrinsic feature of a time series is that, typically, adjacent observations are dependent. The nature of this dependence
among observations of a time series is of considerable practical interest. Time series analysis is concerned with techniques
for the analysis of this dependence. (Box et al. 1994p. 1) 相似文献
12.
Helmut Herwartz 《AStA Advances in Statistical Analysis》2011,95(2):147-168
This paper describes the performance of specific-to-general composition of forecasting models that accord with (approximate)
linear autoregressions. Monte Carlo experiments are complemented with ex-ante forecasting results for 97 macroeconomic time
series collected for the G7 economies in Stock and Watson (J. Forecast. 23:405–430, 2004). In small samples, the specific-to-general strategy is superior in terms of ex-ante forecasting performance in comparison
with a commonly applied strategy of successive model reduction according to weakest parameter significance. Applied to real
data, the specific-to-general approach turns out to be preferable. In comparison with successive model reduction, the successive
model expansion is less likely to involve overly large losses in forecast accuracy and is particularly recommended if the
diagnosed prediction schemes are characterized by a medium to large number of predictors. 相似文献
13.
For multiway contingency tables, Wall and Lienert (Biom. J. 18:259–264, 1976) considered the point-symmetry model. For square contingency tables, Tomizawa (Biom. J. 27:895–905, 1985) gave a theorem that the point-symmetry model holds if and only if both the quasi point-symmetry and the marginal point-symmetry
models hold. This paper proposes some quasi point-symmetry models and marginal point-symmetry models for multiway tables,
and extends Tomizawa’s (Biom. J. 27:895–905, 1985) theorem into multiway tables. We also show that for multiway tables the likelihood ratio statistic for testing goodness
of fit of the point-symmetry model is asymptotically equivalent to the sum of those for testing the quasi point-symmetry model
with some order and the marginal point-symmetry model with the corresponding order. An example is given. 相似文献
14.
Martin Slawski 《Statistics and Computing》2012,22(1):153-168
In view of its ongoing importance for a variety of practical applications, feature selection via ℓ
1-regularization methods like the lasso has been subject to extensive theoretical as well empirical investigations. Despite
its popularity, mere ℓ
1-regularization has been criticized for being inadequate or ineffective, notably in situations in which additional structural
knowledge about the predictors should be taken into account. This has stimulated the development of either systematically
different regularization methods or double regularization approaches which combine ℓ
1-regularization with a second kind of regularization designed to capture additional problem-specific structure. One instance
thereof is the ‘structured elastic net’, a generalization of the proposal in Zou and Hastie (J. R. Stat. Soc. Ser. B 67:301–320,
2005), studied in Slawski et al. (Ann. Appl. Stat. 4(2):1056–1080, 2010) for the class of generalized linear models. 相似文献
15.
In this paper we present a review of population-based simulation for static inference problems. Such methods can be described as generating a collection of random variables {X
n
}
n=1,…,N
in parallel in order to simulate from some target density π (or potentially sequence of target densities). Population-based simulation is important as many challenging sampling problems
in applied statistics cannot be dealt with successfully by conventional Markov chain Monte Carlo (MCMC) methods. We summarize
population-based MCMC (Geyer, Computing Science and Statistics: The 23rd Symposium on the Interface, pp. 156–163, 1991; Liang and Wong, J. Am. Stat. Assoc. 96, 653–666, 2001) and sequential Monte Carlo samplers (SMC) (Del Moral, Doucet and Jasra, J. Roy. Stat. Soc. Ser. B 68, 411–436, 2006a), providing a comparison of the approaches. We give numerical examples from Bayesian mixture modelling (Richardson and Green,
J. Roy. Stat. Soc. Ser. B 59, 731–792, 1997). 相似文献
16.
Jens Hogrefe 《AStA Advances in Statistical Analysis》2008,92(3):271-296
Releases of GDP data undergo a series of revisions over time. These revisions have an impact on the results of macroeconometric
models documented by the growing literature on real-time data applications. Revisions of U.S. GDP data can be explained and
are partly predictable according to Faust et al. (J. Money Credit Bank. 37(3):403–419, 2005) or Fixler and Grimm (J. Product. Anal. 25:213–229, 2006). This analysis proposes the inclusion of mixed frequency data for forecasting GDP revisions. Thereby, the information set
available around the first data vintage can be better exploited than the pure quarterly data. In-sample and out-of-sample
results suggest that forecasts of GDP revisions can be improved by using mixed frequency data. 相似文献
17.
Yves F. Atchadé 《Statistics and Computing》2011,21(4):463-473
In empirical Bayes inference one is typically interested in sampling from the posterior distribution of a parameter with a
hyper-parameter set to its maximum likelihood estimate. This is often problematic particularly when the likelihood function
of the hyper-parameter is not available in closed form and the posterior distribution is intractable. Previous works have
dealt with this problem using a multi-step approach based on the EM algorithm and Markov Chain Monte Carlo (MCMC). We propose
a framework based on recent developments in adaptive MCMC, where this problem is addressed more efficiently using a single
Monte Carlo run. We discuss the convergence of the algorithm and its connection with the EM algorithm. We apply our algorithm
to the Bayesian Lasso of Park and Casella (J. Am. Stat. Assoc. 103:681–686, 2008) and on the empirical Bayes variable selection of George and Foster (J. Am. Stat. Assoc. 87:731–747, 2000). 相似文献
18.
Vasyl Golosnoy Sergiy Ragulin Wolfgang Schmid 《AStA Advances in Statistical Analysis》2009,93(3):263-279
The multivariate CUSUM#1 control chart of Pignatiello and Runger (J. Qual. Technol. 22:173–186, 1991) is widely used in practical applications due to its good ability to detect shifts of small and medium size in a process
of interest. This paper investigates properties and suggests several refinements of this chart. The performance of the competing
procedures is evaluated within a Monte Carlo simulation study. The suggested log MCUSUM chart proves to be the best among
the investigated alternatives for the considered performance criteria. 相似文献
19.
This paper examines the finite-sample behavior of the Lagrange Multiplier (LM) test for fractional integration proposed by
Breitung and Hassler (J. Econom. 110:167–185, 2002). We find by extensive Monte Carlo simulations that size distortions can be quite large in small samples. These are caused
by a finite-sample bias towards the alternative. Analytic expressions for this bias are derived, based on which the test can
easily be corrected. 相似文献
20.
Chih-Kang Chu Jhao-Siang Siao Lih-Chung Wang Wen-Shuenn Deng 《Statistics and Computing》2012,22(1):17-31
A new procedure is proposed to estimate the jump location curve and surface in the two-dimensional (2D) and three-dimensional
(3D) nonparametric jump regression models, respectively. In each of the 2D and 3D cases, our estimation procedure is motivated
by the fact that, under some regularity conditions, the ridge location of the rotational difference kernel estimate (RDKE;
Qiu in Sankhyā Ser. A 59, 268–294, 1997, and J. Comput. Graph. Stat. 11, 799–822, 2002; Garlipp and Müller in Sankhyā Ser. A 69, 55–86, 2007) obtained from the noisy image is asymptotically close to the jump location of the true image. Accordingly, a computational
procedure based on the kernel smoothing method is designed to find the ridge location of RDKE, and the result is taken as
the jump location estimate. The sequence relationship among the points comprising our jump location estimate is obtained.
Our jump location estimate is produced without the knowledge of the range or shape of jump region. Simulation results demonstrate
that the proposed estimation procedure can detect the jump location very well, and thus it is a useful alternative for estimating
the jump location in each of the 2D and 3D cases. 相似文献