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A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary -- everything is contained in this archive. The C-code computes the DWT and maximal overlap
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Calculate any of 6 different ICCs with confidence intervals
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Plots a shaded region a graph between specified lower and upper confidence intervals (L and U).
l and u must be vectors of the same length.-Plots a shaded region on a graph between specified lower and upper confidence intervals (L and U).
l and
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当对两个核酸序列进行比对时，K-Estimator用来评估两者核苷酸替代数（趋异性），包括蛋白编码区与非蛋白编码区。使用Monte Carlo模拟估算可信区间。在分子进化研究中，评估两条核酸序列的被替换核苷酸数量是一个中心课题。精确量化这些数据将直接影响广泛应用于进化基因学的许多实验的可靠性。-When the two nucleic acid sequences, when compared, K-Estimator used to assess the number of nucleotid
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Calc standard error of the mean or non-parametric confidence intervals for samples of a time series
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Myplotyy情节不同的数据集具有共同的X轴使用一个数字，但个别的Y轴。
每一个曲线（Y轴）的属性可单独调整，为线性或对数尺度，正常或反向规模，置信区间等，颜色，曲线标签，...
见截图和运行示例“myplotyy_example.m”在zip文件中。
-Myplotyy plots different data sets with a common x-axis but using individual y-axes in one figure.
The proper
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汽车高斯曲面拟合
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2程序，以适应到表面二维高斯：
子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的
这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。
autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。
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对采集的样例数据进行回归分析，包括一元、多元和病态回归三种情况，并在一定执行概率给出置信区间和回归预测-The collected sample data, regression analysis, including a dollar return of three cases and pathological diversity, and given a certain probability of confidence intervals and perform regression
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When the two nucleic acid sequences, when compared, K-Estimator used to assess the number of nucleotide substitutions between the two (Divergent), including the protein coding region and non-protein coding region. Using Monte Carlo simulation estimat
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DNA 蛋白质分析工具，主要用于功能分化研究-When the two nucleic acid sequences, when compared, K-Estimator used to assess the number of nucleotide substitutions between the two (Divergent), including the protein coding region and non-protein coding region. Using Monte C
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自适应邻域技术在图像处理方面运用的非常广泛，本文中所介绍的两种自适应邻域技术——各向异性局部多项式近似—置信区域交集[1] (LPA-ICI，Local Polynomial Approximation—Intersection of Confidence Intervals)技术和区域生长[2] (region growing)技术是目前为止使用最为广泛两种。本文分别使用点的灰度值预选取、矩形块的均值预选取和自适应块预选取来驱动这两种自适应邻域算法来实现自适应邻域的生成，并将自适应邻域技术
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This report explains the queuing systems in a small clinic which has two types of queuing systems and can be denoted by Kendall’s notation M/U/1 and M/M/2.
The confidence intervals for necessary queuing parameters are calculated for both of the que
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粒子滤波的一个算例，包含与EKF的对比以及置信区间的估计-The example is the particle filter, including comparison with EKF estimates and confidence intervals
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Statistical intervals can be confusing, even in the minds of those who use
them often. This paper uses an example to describe the differences between
confidence intervals, prediction intervals and tolerance intervals.
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调用normfit函数求正态总体参数的最大似然估计和置信区间-Normfit function calls seeking normal population parameters of maximum likelihood estimates and confidence intervals
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时间序列分析，AR模型，用于流数据预测与滤波
输入参数：y为原始数据矩阵，p为AR模型的阶数，la为自回归模型的遗忘系数
输出参数：预测值，置信区间，离群点等-Time series analysis, AR model for prediction and filtering data stream input parameters: y original data matrix, p is the order of the AR model, la self-forgetting c
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支持向量机工具箱By Kris De Brabanter,标准的非参数回归，健壮的回归，一些调优标准等经典交叉验证，较好的交互性-The StatLSSVM toolbox is written so that only a few lines of code are necessary in order to perform standard nonparametric regression, regression with correlated errors and robust regre
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Computes a set of t-distribution based confidence intervals for the estimated means of the columns of a matrix.
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M-functions for unified tidal analysis of sea level or currents, with the ability to handle irregularly distributed and/or gappy times; accurate nodal/satellite corrections for multi-year records; confidence intervals based on residual spectra; and c
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反演问题的误差椭球及及在各个模型空间的投影，应用与得到模型参数的置信区间。-Error ellipsoid and the inverse problem and the projection of each model space, the application of the model parameters and obtain confidence intervals.
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