常用的数学统计算法，希望大家喜欢 Calculate the approximation of the standard normal distributi...

这是一个比较实用的最小二乘法，涵盖了最小二乘法的基本内容，通过学习本代码，可以掌握最小二乘法的精华，为以后的数据平差打下一个基础。

基于MFC的CBitsets类，可实现二进制，八进制，十六进制等之间相互转换显示等

小波提升格式的java源代码，包括标准的分裂、预测和更新三步，以及一个实例-Lifting format java source code, including the standard split, forecasts and updates of steps, and an example

用C＋＋实现的高斯混合模型的算法类，方差矩阵是对角矩阵-C++ Gaussian mixture model algorithm category, variance matrix is diagonal matrix

地图四染色问题 map.in为输入文件，文本格式，地图的邻接矩阵-map map.in four staining problem for the importation documents, text format, maps the adjacency matrix

大学里必学的一门课程，数值分析的一个必做的程序，拉格朗日一次插值-universities will learn a curriculum, a numerical analysis of the process will do, Lagrange interpolation.

应用背景这个函数生成开始，在已知的周数的最后日期范围关键技术使用此函数创建MySQL查询或其他范围的搜索数据的日期。在查询一些功能只能在特定的月年周搜索不周。所以，这个功能可以帮助你做这个。

This is the project of my course in the USA: Customers arrive at a service station (with a single server) according to the Poisson process with a mean arrival rate of lambda = 0.3 (customers/min). Each customer waits in queue (if present), proceeds to receive service upon his/her turn, and departs the system when the service is completed. The service time is uniformly distributed between 2.5 and 4.5 minutes. On each day, the service station is open for two hours. Any customers in queue at the end of work hours are served before closing the service station for the day. Use simulation (do 100 simulation runs) to determine

自己编写的一个小计算器，和大家一起共享探讨-I have written a small calculator, and the community together to explore shared

平均因子分解法，适用于正定矩阵First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X=U U, where U is the square root matrix of X, and satisfies: (1) U U = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is "positive definite" which guarantees the existence of such kind of decomposition. -Average factor decomposition method applied to positive definite matrix First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X = UU, where U is the square root matrix of X, and satisfies: (1) UU = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is positive