-
PNCC
matlabs program for finding PNCC features
- 2010-12-16 13:11:11下载
- 积分:1
-
三维装箱MATLAB程序
说明: Some common algorithms
- 2020-11-14 19:29:41下载
- 积分:1
-
lmd
说明: LMD,局部均值分解算法,主要用于对振动信号进行分析,不需要设置分解参数(LMD, a local mean decomposition algorithm, is mainly used to analyze vibration signals without setting decomposition parameters.)
- 2019-02-18 16:47:22下载
- 积分:1
-
Ionosphere_LR
说明: 电离层的贝叶斯分类器,使用matlab编程开发,具有正确率高的优点(Ionosphere Bayesian classifier, using the matlab program development, the advantages with the correct rate)
- 2010-05-04 19:27:25下载
- 积分:1
-
m4
说明: thanks it useful ihope to used
- 2009-11-13 11:53:46下载
- 积分:1
-
minimum-variance-self-tuning-control
用matlab实现自适应控制中的最小方差自校正控制(Minimum variance adaptive control self-tuning control using matlab)
- 2012-11-19 10:15:53下载
- 积分:1
-
leixingzhuanhuan
GUI系统进行图像的类型转换,能够吧图像转换成不同的格式。(GUI system for image conversion, it can convert images into a different format.)
- 2014-01-26 10:13:44下载
- 积分:1
-
bootgmregress
自举是一种由重采样估计,独立和(蒙特卡洛重采样)等概率设置一个单一的数据统计变化的一个途径。允许的措施估计那里的潜在分布是未知的或者样本量很小。他们的结果与这些分析方法的统计特性相一致。
在这里,我们使用非参数逼近。非参数引导更简单。它不使用该模型的结构,建造人工数据。矢量[易西]是重采样,而不是直接与replecement。这些参数是从这些对构建。
二,回归模型时,应使用在回归方程中的两个变量是随机的,会有错误的,即不是由研究者控制。模式,我用普通最小二乘回归低估了变量之间的错误时,他们都含有线性关系的斜率。据索卡尔和罗尔夫(1995),模型二回归的主题是一对哪些研究和争论仍在继续,最终建议是很难做出。
BOOTGMREGRESS模型II是一个引导程序。这需要s引导和规范样品前坡计算变量。这两个变量的每个转化为具有零均值和标准差的一个。由此产生的斜率是线性回归系数的Y在X里克创造了这个词(1973)几何平均数并给出了一个模型II回归广泛审查。它也被称为引导标准的主要轴线(The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is unknown or where sample sizes are small. Their results are consistent with the statistical properties of those analytical methods.
Here, we use the Non-parametric Bootstrap. Non-parametric bootstrap is simpler. It does not use the structure of the model to construct artificial data. The vector [yi, xi] is instead directly resampled with replecement. The parameters are constructed from these pairs.
Model II regression should be used when the two variables in the regression equation are random and subject to error, i.e. not controlled by the researcher. Model I regression using ordinary least squares underestimates the slope of the linear relationship between the variables when they both contain error. According to Sokal and Rohlf (1995), t)
- 2011-05-21 13:19:38下载
- 积分:1
-
Mercurial_The_Definitive_Guide
mercurial 分布式版本控制软件指南,方便个人和工程使用,使用方便(mercurial distributed version control software)
- 2013-08-11 17:33:24下载
- 积分:1
-
PSS-thesis
Sparsity-Promoting Optimal Wide-Area Control of Power Networks
- 2014-10-31 19:00:54下载
- 积分:1