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151.
§ 1.Introduction and Notations In this paper,for any given matrices A and B,A B denotes the Kronecker productof A and B,A is a vector formed by stacking the columns of A under each other,μ(A)is a space generated by the columns of A,and PA=A(A′A) - A′. Fourthmore,if A andB are square matrices,then A>B and A≥ B mean that A-B is a symmetrical positiveand nonnegative matrix,respectively,andλi(A) is the i-th largest eigenvalue of A. Consider general multivariate linear modelY … 相似文献
152.
153.
The paper studies a generalized linear model(GLM)y_t = h(x_t~T β) + ε_t,t = l,2,...,n,where ε_1 = η_1,ε_1 =ρε_t +η_t,t = 2,3,...;n,h is a continuous differentiable function,η_t's are independent and identically distributed random errors with zero mean and finite variance σ~2.Firstly,the quasi-maximum likelihood(QML) estimators of β,p and σ~2 are given.Secondly,under mild conditions,the asymptotic properties(including the existence,weak consistency and asymptotic distribution) of the QML estimators are investigated.Lastly,the validity of method is illuminated by a simulation example. 相似文献
154.
Let ∏1,…,∏k denote k independent populations, where a random observation from population ∏ i has a uniform distribution over the interval (0,θ i ) and θ i is a realization of a random variable having an unknown prior distribution G i . Population ∏ i is said to be a good population if θ i ≥θ0, where θ0 is a given, positive number. This paper provides a sequence of empirical Bayes procedures for selecting the good populationsamong ∏1,…,∏ k . It is shown that these procedures are asymptotically optimal and that the order of associated convergence rates is O(n-r/4) for some r, 0<r<2, where n is the number of accumulated past observations at hand 相似文献
155.
《Journal of computational and graphical statistics》2013,22(1):186-200
We introduce fast and robust algorithms for lower rank approximation to given matrices based on robust alternating regression. The alternating least squares regression, also called criss-cross regression, was used for lower rank approximation of matrices, but it lacks robustness against outliers in these matrices. We use robust regression estimators and address some of the complications arising from this approach. We find it helpful to use high breakdown estimators in the initial iterations, followed by M estimators with monotone score functions in later iterations towards convergence. In addition to robustness, the computational speed is another important consideration in the development of our proposed algorithm, because alternating robust regression can be computationally intensive for large matrices. Based on a mix of the least trimmed squares (LTS) and Huber's M estimators, we demonstrate that fast and robust lower rank approximations are possible for modestly large matrices. 相似文献
156.
《Journal of computational and graphical statistics》2013,22(3):694-716
We introduce a nonparametric nonlinear time series model. The novel idea is to fit a model via penalization, where the penalty term is an unbiased estimator of the integrated Hessian of the underlying function. The underlying model assumption is very general: it has Hessian almost everywhere in its domain. Numerical experiments demonstrate that our model has better predictive power: if the underlying model complies with an existing parametric/semiparametric form (e.g., a threshold autoregressive model (TAR), an additive autoregressive model (AAR), or a functional coefficient autoregressive model (FAR)), our model performs comparably; if the underlying model does not comply with any preexisting form, our model outperforms in nearly all simulations. We name our model a Hessian regularized nonlinear model for time series (HRM). We conjecture on theoretical properties and use simulations to verify. Our method can be viewed as a way to generalize splines to high dimensions (when the number of variates is more than three), under which an analogous analytical derivation cannot work due to the curse of dimensionality. Supplemental materials are provided, and will help readers reproduce all results in the article. 相似文献
157.
158.
刘金山 《纯粹数学与应用数学》1997,13(1):30-37
考虑相依回归方程系统yi=Xiβi+εi(i=1,2),E(εi)=0,Cov(εi,εj)=σijIn。记βi为βi的协方差改进估计^[1]。σij未知时,记βi为用非限定估计σij代替βi中的σij得到的两步估计,并记βi为用限定估计σij代替βi中的σij得到的两步估计,这两种两步估计的协方差中含有未知参数σij代替βi中的σij得到的两步估计,这两种两步估计的协方差中含有未知参数σij。本 相似文献
159.
韦来生 《高校应用数学学报(A辑)》1997,(2):163-174
本文考虑单向分类的方差分析模型,构造了P′α的线性Bayes估计和经验Bayes(EB)估计,此处αa×1是效应参数向量,Pa×k是常数矩阵.在较一般的条件下,基于均方误差矩阵准则和PitmanCloseness准则,我们分别证明了EB估计优于最小二乘估计 相似文献
160.
指数分布场合下步进应力加速寿命试验的Bayes分析 总被引:5,自引:0,他引:5
张志华 《高校应用数学学报(A辑)》1997,(2):175-182
当寿命分布为指数分布时,本文给出了步进应力加速寿命试验的一种新的Bayes估计,为计算上的方便,本文还给出一种近似方法,数值例子表明,此方法简便可行。 相似文献