Allan方差分析MATLAB代码，含MPU6050八小时静态数据，测试运行成功了的

线性统计模型 线性回归与方差分析 这对于准备从事大数据分析的人来说是必修的一门课程

详细介绍了极化SAR数据协方差的pauli分解方法含代码

NSGA2优化算法Matlab求解多目标优化问题，遗传算法优化+帕累托排序，有效地解决了多目标优化问题，算例可行有效。

可以直接运行代码，对于进行遥感图像评价的人来说，很方便啦已经

用matlab编写的，用于求图像的均值、方差、标准差，可以直接运行

运用地统计学进行空间分析基本包括以下几个步骤，即数据探索性分析，空间连续性的量化模型，未知点属性值的估计，对未知点局部及空间整体不确定性的预测。

http://www.mathworks.com/matlabcentral/fileexchange/25986-constrained-particle-swarm-optimization Description Previously titled "Another Particle Swarm Toolbox" Introduction Particle swarm optimization (PSO) is a derivative-free global optimum solver. It is inspired by the surprisingly organized behaviour of large groups of simple animals, such as flocks of birds, schools of fish, or swarms of locusts. The individual creatures, or "particles", in this algorithm are primitive, knowing only four simple things: 1 & 2) their own current location in the search space and fitness value, 3) their previous personal best location, and 4) the overall best location found by all the particles in the "swarm". There are no gradients or Hessians to calculate. Each particle continually adjusts its speed and trajectory in the search space based on this information, moving closer towards the global optimum with each iteration. As seen in nature, this computational swarm displays a remarkable level of coherence and coordination despite the simplicity of its individual particles. Ease of Use If you are already using the Genetic Algorithm (GA) included with MATLAB's Global Optimization Toolbox, then this PSO toolbox will save you a great deal of time. It can be called from the MATLAB command line using the same syntax as the GA, with some additional options specific to PSO. This will allow a high degree of code re-usability between the PSO toolbox and the GA toolbox. Certain GA-specific parameters such as cross-over and mutation functions will obviously not be applicable to the PSO algorithm. However, many of the commonly used options for the Genetic Algorithm Toolbox may be used interchangeably with PSO since they are both iterative population-based solvers. See >> help pso (from the ./psopt directory) for more details. Features * NEW: support for distributed computing using MATLAB's parallel computing toolbox. * Full support for bounded, linear, and nonlinear constraints. *

poisson(泊松过程)的Matlab仿真包括poisson分布，及相关函数，平均值，均方差等

基于NSGA-2思想的多目标优化程序，采用进化算法处理多目标实值优化问题