——不妨试试 响应面分析法 (response surface methodology，记为 RSM)！ 大家都学过泰勒分析，其思想就是用多项式来拟合任意函数，比方说自然指数函数，我们可以进行如下展开： e^x=1+x+\frac {x^2} {2!}+\frac {x^3} {3!}+\frac {x^4} {4!}+... 如果要求不是很严格，我们其实可以只用前几项来表达，如下图所示： 可见，对于指数函数而言，在 [0 1]范围内，多项式取到三次的时候就和真值比较接近了，也就说说我们可以用更容易处理的多项式来拟合函数。 但是， 泰勒 …

In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. RSM is an empirical model which employs the use of mathematical and statistical techniques to relate input variables, otherwise known as factors, to the response.

响应曲面设计是用来研究因子 (影响因素X)与过程输出 (响应变量Y)之间是否存在二次项关系，进而找出因子最优配置的一种试验方法。 1 应用 寻找产生“ 最佳”响应的因子设置； 寻找满足操作或过程规范的因子设置； …

Here the objective of Response Surface Methods (RSM) is optimization, finding the best set of factor levels to achieve some goal. This lesson aims to cover the following goals: The text has a graphic depicting a response surface method in three dimensions, though actually it is four dimensional space that is being represented since the three ...

2019年5月15日 · · 一款 .NET 开源、功能强大的远程连接管理工具，支持 RDP、VNC、SSH 等多种主流协议！ 先开题，慢慢补充。 参考： 什么是响应面（RSM）分析 Response-Surface Methods in R, Using rsm In-class Examples with R Code Response Surface Analysis (RSM) Lesson 11: Response.

While designed with rsm objects in mind, these methods work with any lm object and thus provide a quick way to graph a fitted surface. Enhancements include coloring, adding contour lines to perspective plots, and hooks that provide additional annotations.

This tutorial illustrates Stat-Ease ® software tools for applying split-plot design to response surface method (RSM) experiments for process optimization. In many experiments, the levels of one or more factors are hard to change.

ANSYS Workbench evaluates the goodness of fit from response levels (RSM) according to the unique goodness of fit diagram. This criterion indicates the degree of proportionality or similarity between the values obtained from the solution process at the design point in the test environment (DOE) with the points on the response surface estimated ...

响应曲面设计是利用合理的试验设计方法并通过实验得到一定数据，采用多元二次回归方程来拟合因素与响应值之间的函数关系，通过对回归方程的分析来寻求最优工艺参数，解决多变量问题的一种统计方法。 适用条件与范围：确信或怀疑因素对指标存在非线性影响；因素个数2-7个，一般不超过4个；所有因素均为计量值数据；试验区域已接近最优区域；基于2水平的全因子正交试验。

Diagnostics: Examine diagnostic graphs to validate model. Model Graphs: If model adequately represents response, generate contour and 3D plots. Confirmation: Verify the model predictions with confirmation runs. Do not select an aliased model!