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排序方式: 共有1135条查询结果,搜索用时 15 毫秒
1.
Laurent Gardes Stéphane Girard Gilles Stupfler 《Scandinavian Journal of Statistics》2020,47(3):922-949
The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail Lp-medians encompassing the MS and CTE. For p in (1,2), a tail Lp-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data. 相似文献
2.
Abstract. We correct two proofs concerning Markov properties for graphs representing marginal independence relations. 相似文献
3.
The plant ‘Heat Rate’ (HR) is a measure of overall efficiency of a thermal power generating system. It depends on a large number of factors, some of which are non-measurable, while data relating to others are seldom available and recorded. However, coal quality (expressed in terms of ‘effective heat value’ (EHV) as kcal/kg) transpires to be one of the important factors that influences HR values and data on EHV are available in any thermal power generating system. In the present work, we propose a prediction interval of the HR values on the basis of only EHV, keeping in mind that coal quality is one of the important (but not the only) factors that have a pronounced effect on the combustion process and hence on HR. The underlying theory borrows the idea of providing simultaneous confidence interval (SCI) to the coefficients of a p-th p(≥1) order autoregressive model (AR(p)). The theory has been substantiated with the help of real life data from a power utility (after suitable base and scale transformation of the data to maintain the confidentiality of the classified document). Scope for formulating strategies to enhance the economy of a thermal power generating system has also been explored. 相似文献
4.
Summary Weak disintegrations are investigated from various points of view. Kolmogorov's definition of conditional probability is critically
analysed, and it is noted how the notion of disintegrability plays some role in connecting Kolmogorov's definition with the
one given in line with de Finetti's coherence principle. Conditions are given, on the domain of a prevision, implying the
equivalence between weak disintegrability and conglomerability. Moreover, weak sintegrations are characterized in terms of
coherence, in de Finetti's sense, of, a suitable function. This fact enables us to give, an interpretation of weak disintegrability
as a form of “preservation of coherence”. The previous results are also applied to a hypothetical inferential problem. In
particular, an inference is shown to be coherent, in the sense of Heath and Sudderth, if and only if a suitable function is
coherent, in de Finetti's sense.
Research partially supported by: M.U.R.S.T. 40% “Problemi di inferenza pura”. 相似文献
5.
A. Baddeley R. Turner J. Møller M. Hazelton 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2005,67(5):617-666
Summary. We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction. 相似文献
6.
Summary The paper deals with missing data and forecasting problems in multivariate time series making use of the Common Components
Dynamic Linear Model (DLMCC), presented in Quintana (1985), and West and Harrison (1989).
Some results are presented and discussed: exploiting the correlation between series, estimated by the DLMCC, the paper shows
as it is possible to update state vector posterior distributions for the unobserved series. This is realized on the base of
the updating of the observed series state vectors, for which the usual Kalman filter equations can be applied.
An application concerning some Italian private consumption series provides an example of the model capabilities. 相似文献
7.
Gini’s nuclear family 总被引:1,自引:0,他引:1
Rolf Aaberge 《Journal of Economic Inequality》2007,5(3):305-322
The purpose of this paper is to justify the use of the Gini coefficient and two close relatives for summarizing the basic
information of inequality in distributions of income. To this end we employ a specific transformation of the Lorenz curve,
the scaled conditional mean curve, rather than the Lorenz curve as the basic formal representation of inequality in distributions
of income. The scaled conditional mean curve is shown to possess several attractive properties as an alternative interpretation
of the information content of the Lorenz curve and furthermore proves to yield essential information on polarization in the
population. The paper also provides asymptotic distribution results for the empirical scaled conditional mean curve and the
related family of empirical measures of inequality.
相似文献
8.
Catriona M. Queen Ben J. Wright Casper J. Albers 《Australian & New Zealand Journal of Statistics》2007,49(3):221-239
The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM. 相似文献
9.
The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software. 相似文献
10.
Abstract. This paper reviews some of the key statistical ideas that are encountered when trying to find empirical support to causal interpretations and conclusions, by applying statistical methods on experimental or observational longitudinal data. In such data, typically a collection of individuals are followed over time, then each one has registered a sequence of covariate measurements along with values of control variables that in the analysis are to be interpreted as causes, and finally the individual outcomes or responses are reported. Particular attention is given to the potentially important problem of confounding. We provide conditions under which, at least in principle, unconfounded estimation of the causal effects can be accomplished. Our approach for dealing with causal problems is entirely probabilistic, and we apply Bayesian ideas and techniques to deal with the corresponding statistical inference. In particular, we use the general framework of marked point processes for setting up the probability models, and consider posterior predictive distributions as providing the natural summary measures for assessing the causal effects. We also draw connections to relevant recent work in this area, notably to Judea Pearl's formulations based on graphical models and his calculus of so‐called do‐probabilities. Two examples illustrating different aspects of causal reasoning are discussed in detail. 相似文献