[Stata]演示教程命令集及Pyramid命令修改

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收藏 2015-08-15

命令	演示教程内容（自学专用）	附件
aboutreg	回归分析	aboutreg.rar 大小:(8.6 KB) 马上下载本附件包括： aboutreg.tut
bstrap /bstut	自助法	bstrap.rar 大小:(6.2 KB) 马上下载本附件包括： bstrap.tut
pyramid	人口金字塔	pyramid.rar 大小:(6.98 KB) 马上下载
randwalk /tt7	随机游走	randwalk.rar 大小:(3.42 KB) 马上下载本附件包括： randwalk.hlp randwalk.tut
sqc1/pca	计算工序能力指数Process Capability Indices(PCIs)	sqc1.zip 大小:(4.47 KB) 马上下载本附件包括： cylinder.dat pca.tut pciest.ado pciest.hlp

复制代码

安装使用：

1.command窗口输入cd或pwd
2.将附件解压到当前工作路径
2.在command窗口输入 tutorial 命令名
3.然后按Enter键不断执行

注：

pyramid.tut在运行时出现codebook错误：
解决方法1.运行aboutreg.tut后再运行,
解决方法2.使用如下代码（即保存为do文档代替演示，见附件)
解决方法3.对原命令进行修改，遇错后继续执行（见9楼）：

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命令	作者
abooutreg	Stanislav Kolenikov
pyramid	Jens M.Lauritsen: (v1.02)
randwalk	Albert Verbeek/Jeroen Weesie
bstrap	Stanislav Kolenikov
pca/sqc1	Sutaip L. C. Saw and Teck Wong Soon

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rrjj101022

2015-8-15 11:08:16

谢谢分享~~~

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niuniuyiwan

2015-8-18 15:43:31

2	. tutorial bstrap
3
4
5	The bootstrap methods
6	Stanislav Kolenikov
7	skolenik@recep.glasnet.ru
8	------------------------------------------------
9
10
11
12
13	This tutorial can be discontinued at any time by pressing Break (Ctrl-Break at
14	the keyboard or Break icon at the toolbar. Press Enter or Space when you see
15	--more-- message.
16
17
18
19
20	This tutorial overviews the main uses of the bootstrap procedures in
21	econometric practice. The Stata commands to be discussed are:
22
23	bs bstrap bstat bsample
24
25	You can get a more detailed information on each of them by invoking
26	help bs from Stata prompt after the tutorial session.

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niuniuyiwan

2015-8-18 18:07:49

1
2	. tutorial aboutreg
3
4
5
6
7	Regression and so on
8	Stanislav Kolenikov
9	skolenik@unc.edu
10	------------------------------------------------
11
12
13
14
15	-------------------------------------------------------------------------------
16	In this tutorial we shall discuss some regression diagnostic techniques
17	and some regression remedies such as heteroskedasticity correction and
18	transformation of the dependent variable towards normality.
19
20	If you are continuing or repeating this tutorial, input the number of the
21	part you stopped last time, or just press Enter to continue:
22
23	1. From the very beginning
24	2. First regression -- naive and primitive OLS
25	3. Regression diagnostics commands
26	4. Tests for heteroskedasticity
27	5. Tests for nonlinearity
28	6. Tests for multicollinearity
29	7. Normality of residuals
30	8. Heteroskedasticiy correction
31	9. Transformation towards normality for the dependent variable
32
33	Now, please press the number of the section or Enter to continue:

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niuniuyiwan

2015-8-18 18:10:04

1	. tutorial randwalk
2
3
4	---------------------------------------------------------------------------
5	Tutorial on random walks (Albert Verbeek/Jeroen Weesie)
6
7	This tutorial displays some discrete time random walks in 1 and 2
8	dimensions, illustrating the use of graph and the use of random numbers. If
9	you run the demo more than once, you will get different graphs each time.
10
11	First a one-dimensional, normal random walk
12	---------------------------------------------------------------------------
13
14	. set obs 500 /* 500 observations */
15	number of observations (_N) was 0, now 500
16	. gen int t = _n /* t = time */
17	. lab var t time = _n
18	. gen sumz = sum(invnorm(uniform())) /* to be explained shortly */
19
20	---------------------------------------------------------------------------
21	Explanation:
22
23	uniform() generates a random number from the uniform distribution on (0,1).
24	If it is transformed by the inverse of the cumulative distribution of a
25	random variable X, the result will have the same distribution as X. Here,
26	invnorm() is the inverse of the cumulative standard normal distribution.
27	So invnorm(uniform()) is a standard-normally distributed random number.
28	By taking the sum(), we get a random walk: a sum of independently and
29	identically distributed random numbers.
30	---------------------------------------------------------------------------

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niuniuyiwan

2015-8-18 18:26:04

1	. tutorial pca
2
3
4
5
6
7	PROCESS CAPABILITY ANALYSIS USING STATA
8	---------------------------------------
9
10
11	In this tutorial, we show how to use Stata to perform a process capability
12	analysis of a subset of some data in DeVor, Chang & Sutherland (1992). It
13	consists of (coded) measurements of the inside diameter of machined cylinder
14	bores obtained in 31 samples, each of size 5. The (coded) lower and upper
15	specification limits are 195 and 203, respectively.
16
17	We begin the analysis by using Stata's xchart and rchart commands to determine
18	whether the process is in control. If so, we then estimate the following
19	summary measures:
20	- process mean and standard deviation
21	- process capability indices
22	- fraction nonconforming
23	- percent yield
24
25	We also plot a histogram of the measurements and perform a Shapiro-Wilk test
26	for normality.
27
28	. infile x1-x5 using cylinder.dat
29	(31 observations read)

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