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与表型相关的基因区域异质性非参数检验AI 解读

High-dimensional statistical problems arise in the investigation of the relationship between reduced sensitivity to antiretroviral drugs among human immunodeficiency virus-infected patients and viral genotypic patterns obtained from blood samples. This article develops a nonparametric approach for analyzing gene region heterogeneity associated with drug-resistance phenotype. The method is based on the distribution of distances between viral genetic sequences. The distance…

通过生成函数计算置换分布及离散数据敏感性分析AI 解读

Generating functions provide a simple and elegant way to describe probability or frequency distributions of discrete statistics and, in particular, permutation distributions. They are also a computational tool. Many efficient algorithms, including those described as fast Fourier transform methods, network methods, and multiple shift methods, are different implementations of the recursions needed to evaluate generating functions efficiently. Our goals here are twofold. First,…

生成函数计算置换分布及离散数据敏感性分析AI 解读

Generating functions provide a simple and elegant way to describe probability or frequency distributions of discrete statistics and, in particular, permutation distributions. They are also a computational tool. Many efficient algorithms, including those described as fast Fourier transform methods, network methods, and multiple shift methods, are different implementations of the recursions needed to evaluate generating functions efficiently. Our goals here are twofold. First,…

精确拟合优度检验的方法AI 解读

Numerous goodness-of-fit tests with asymptotic chi-squared distributions have been proposed for discrete multivariate data, and there has been much discussion about using asymptotic results for computing critical values when there are small expected cell values. Although exact methods would be preferred in these situations, it generally is believed that such methods are computationally intractable. We propose methods for calculating exact distributions and significance…

修剪均值置换分布的高效计算AI 解读

The permutation distribution of the trimmed mean in matched-pairs designs is studied. This statistic is important since it is robust to both outliers and distributional assumptions. A polynomial-time algorithm for this inherently exponential-time problem is presented. The characteristic function of the distribution provides both the basis for the algorithm and a vehicle for calculating the asymptotic permutation distribution.

MS/PC-DOS 计算机上的生存分析软件AI 解读

Abstract There exist more than a dozen MS/PC‐DOS programs with the capability of performing some form of survival analysis. Most of these are reviewed here, with respect to (1) the survival analysis methods they cover, (2) their ease of use and flexibility, (3) their user interface, (4) their graphics capabilities, and (5) their computational accuracy.

含大小单元格计数的列联表分析方法AI 解读

The traditional practice has been to analyze contingency tables using asymptotic χ2 approximations for the tail probability of certain test statistics even when the approximation is known to be poor. For two-dimensional tables Pearson's X 2 statistic is most commonly used, whereas for multidimensional tables the likelihood ratio test is preferred because it makes it easy to test series of nested hypotheses. When asymptotic approximations are not adequate, exact tests are…

含大、小单元格计数的列联表分析方法AI 解读

The traditional practice has been to analyze contingency tables using asymptotic χ2 approximations for the tail probability of certain test statistics even when the approximation is known to be poor. For two-dimensional tables Pearson's X 2 statistic is most commonly used, whereas for multidimensional tables the likelihood ratio test is preferred because it makes it easy to test series of nested hypotheses. When asymptotic approximations are not adequate, exact tests are…

自回归谱的同时置信带AI 解读

A shortcoming in the use of autoregressive spectral estimation has been the lack of methods for placing confidence intervals or bands on the estimated spectral density. We propose and illustrate a method for determining asymptotic simultaneous confidence bands using Scheffé projections.

自回归谱的同时置信带AI 解读

A shortcoming in the use of autoregressive spectral estimation has been the lack of methods for placing confidence intervals or bands on the estimated spectral density. We propose and illustrate a method for determining asymptotic simultaneous confidence bands using Scheffé projections.

确定时间序列周期的一种方法AI 解读

The periods corresponding to peaks in the autoregressive and window spectral density estimators are shown to be consistent and asymptotically normal estimators of peak periods in the true spectral density under assumptions of known autoregressive order and under slight modifications of the assumptions often made to show the asymptotic normality of window estimators, respectively. The asymptotic variances are obtained, and the use of the theory is illustrated by obtaining an…

确定时间序列周期的一种方法AI 解读

The periods corresponding to peaks in the autoregressive and window spectral density estimators are shown to be consistent and asymptotically normal estimators of peak periods in the true spectral density under assumptions of known autoregressive order and under slight modifications of the assumptions often made to show the asymptotic normality of window estimators, respectively. The asymptotic variances are obtained, and the use of the theory is illustrated by obtaining an…

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周期自回归与多元自回归的分析AI 解读

A methodology is presented for analyzing periodic autoregressions which is also applicable when inferring the second order properties of periodically correlated processes. In addition, capitalizing on the connection between periodic and multiple autoregressions, a method is set forth for analyzing the latter, which overcomes the usual requirements of a large number of both parameters and computer storage locations. This is achieved by introducing an orthogonal…

自回归信号加白噪声模型的估计AI 解读

If $x(\bullet)$ is a time series which may be written as $x(t) = s(t) + n(t)$ where $t$ is an integer, $s(\bullet)$ an autoregressive signal of order $q$ and $n(\bullet)$ white noise, then the model has $q + 2$ parameters. These are (i) the $q$ autoregressive parameters (ii) the residual variance of the autoregressive scheme and (iii) the variance of the white noise. A method is proposed to estimate the $q + 2$ parameters. This method is based on analogies with regression…

联合平稳高斯时间序列中循环二次型的近似AI 解读

Let $\{X(t), t = 0, \pm 1, \pm 2,\cdots\}$ be a $p$-dimensional, zero mean, stationary Gaussian time series with matrix-valued covariance function $R(u) = (r_{jk}(u)), u = 0, \pm 1, \pm 2, \cdots; j, k = 1, 2,\cdots, p$. Let $F(\omega)$ be the spectral density matrix of the time series (if $F(\omega)$ exists), and assume that $F(\omega)$ is positive definite for all $\omega\in(0, 2\pi\rbrack$. Let $\hat{F}_X(\omega_l)$ be an estimator of $F(\omega_l)$ formed by averaging $(2n + 1)$…