Bootstrap sampling and estimation
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PEP 439 -- Inclusion of implicit pip bootstrap in Python installation; PEP 439 -- Inclusion of implicit pip bootstrap in Python installation. PEP: 439: Title. The Python community also has an issue of complexity around the current bootstrap procedure for pip and setuptools. They all have their own bootstrap download file with slightly.
- The bootstrap Modal component requires jquery and bootstrap java script files. I forgot to add them in the article. Now I’ve corrected it. Please see points 18 and 19. I’ve added the steps to include jQuery and bootstrap java script files to the master page. The modal popup should work after adding the js files.
- If you have been using the bootstrap RTCS, and you have now installed a permanent RTCS, you can copy the Installation System repository from the bootstrap RTCS to the permanent RTCS. Perform this procedure before starting the Installation System.
- Bootstrap of Stata commands
- Bootstrap of community-contributed programs
- Standard errors and bias estimation
Stata’s programmability makes performing bootstrap sampling and estimation possible (see Efron 1979, 1982; Efron and Tibshirani 1993; Mooney and Duval 1993). We provide two options to simplify bootstrap estimation. bsample draws a sample with replacement from a dataset. bsample may be used in community-contributed programs.
It is easier, however, to perform bootstrap estimation using the bootstrap prefix. bootstrap allows the user to supply an expression that is a function of the stored results of existing commands, or you can write a program to calculate the statistics of interest. bootstrap then can repeatedly draw a sample with replacement, run the community-contributed program, collect the results into a new dataset, and present the results. The community-contributed calculation program is easy to write because every Stata command saves the statistics it calculates.
For instance, assume that we wish to obtain the bootstrap estimate of the standard error of the median of a variable called mpg. Stata's feature calculates and displays summary statistics with summarize; it calculates means, standard deviations, skewness, kurtosis, and various percentiles. Among those percentiles is the 50th percentile—the median. In addition to displaying the calculated results, summarize stores them, and looking in the manual, we discover that the median is stored in r(p50). To get a bootstrap estimate of its standard error, all we need to do is type
. bootstrap r(p50), reps(1000): summarize mpg, detail
and bootstrap will do all the work for us. We'll also specify a seed() option so that you can reproduce our results.
. webuse auto (1978 Automobile Data). bootstrap r(p50), reps(1000) seed(1234): summarize mpg, detail (running summarize on estimation sample) Warning: Because summarize is not an estimation command or does not set e(sample), bootstrap has no way to determine which observations are used in calculating the statistics and so assumes that all observations are used. This means that no observations will be excluded from the resampling because of missing values or other reasons. If the assumption is not true, press Break, save the data, and drop the observations that are to be excluded. Be sure that the dataset in memory contains only the relevant data. Bootstrap replications (1000) (output omitted) Bootstrap results Number of obs = 74 Replications = 1,000 command: summarize mpg, detail _bs_1: r(p50)Observed Bootstrap Normal-based | |
Coef. Std. Err. z P>|z| [95% Conf. Interval] | |
_bs_1 | 20 .9584585 20.87 0.000 18.12146 21.87854 |
Use estat bootstrap to report a table with alternative confidence intervals and an estimate of bias.
. estat bootstrap, all Bootstrap results Number of obs = 74 Replications = 1000 command: summarize mpg, detail _bs_1: r(p50)Observed Bootstrap | |
Coef. Bias Std. Err. [95% Conf. Interval] | |
_bs_1 | 20 .174 .95845847 18.12146 21.87854 (N) |
19 22 (P) | |
19 22 (BC) |
For an example of when we would need to write a program, consider the case of bootstrapping the ratio of two means.
We first define the calculation routine, which we can name whatever we wish,
program myratio, rclass version 16 summarize length local length = r(mean) summarize turn local turn = r(mean) return scalar ratio = `length'/`turn' end
Our program calls summarize and stores the mean of the variable length in a local macro. The program then repeats this procedure for the second variable turn. Finally, the ratio of the two means is computed and returned by our program in the stored result we call r(ratio).
With our program written, we can now obtain the bootstrap estimate by simply typing
This means that we will execute bootstrap with our myratio program for # replications. Below we request 1,000 replications and specify a random-number seed so you can reproduce our results:
. bootstrap r(ratio), reps(1000) seed(4567): myratio (running myratio on estimation sample) Warning: Because myratio is not an estimation command or does not set e(sample), bootstrap has no way to determine which observations are used in calculating the statistics and so assumes that all observations are used. This means that no observations will be excluded from the resampling because of missing values or other reasons. If the assumption is not true, press Break, save the data, and drop the observations that are to be excluded. Be sure that the dataset in memory contains only the relevant data. Bootstrap replications (1000) (output omitted) Bootstrap results Number of obs = 74 Replications = 1,000 command: myratio _bs_1: r(ratio)Observed Bootstrap Normal-based | |
Coef. Std. Err. z P>|z| [95% Conf. Interval] | |
_bs_1 | 4.739945 .0330492 143.42 0.000 4.67517 4.804721 |
The ratio, calculated over the original sample, is 4.739945; the bootstrap estimate of the standard error of the ratio is 0.0344786. Had we wanted to keep the 1,000-observation dataset of bootstrapped results for subsequent analysis, we would have typed
. bootstrap r(ratio), reps(1000) seed(4567) saving(mydata): myratio
bootstrap can be used with any Stata estimator or calculation command and even with community-contributed calculation commands.
We have found bootstrap particularly useful in obtaining estimates of the standard errors of quantile-regression coefficients. Stata performs quantile regression and obtains the standard errors using the method suggested by Koenker and Bassett (1978, 1982). Rogers (1992) reports that these standard errors are satisfactory in the homoskedastic case but that they appear to be understated in the presence of heteroskedastic errors. One alternative is to bootstrap the estimated coefficients to obtain the standard errors. For instance, say that you wish to estimate a median regression of price on variables weight, length, and foreign. Typing qreg price weight length foreign will produce the estimates along with Koenker–Bassett standard errors. To obtain bootstrap standard errors, we could issue the command
. bootstrap, reps(#): qreg price weight length foreign
We recommend this procedure so highly that Gould (1992) wrote a new command in Stata’s programming language to further automate this procedure for quantile regression. Typing bsqreg price weight length foreign will also produce the bootstrapped results.
References
- Efron, B. 1979.
- Bootstrap methods: another look at the jackknife. Annals of Statistics 7: 1–26.
- ------. 1982.
- The Jackknife, the Bootstrap and Other Resampling Plans. Philadelphia: Society for Industrial and Applied Mathematics.
- Efron, B. and R. J. Tibshirani. 1993.
- An Introduction to the Bootstrap. New York: Chapman & Hall.
- Gould, W. 1992.
- sg11.1: Quantile regression with bootstrapped standard errors. Stata Technical Bulletin 9: 19–21. Reprinted in Stata Technical Bulletic Reprints, vol. 2, pp. 137–139.
- Koenker, R., and G. Bassett, Jr. 1978.
- Asymptotic theory of least absolute error regression. Journal of the American Statistical Association 73: 618–622.
- ------. 1982.
- Robust tests for heteroskedasticity based on regression quantiles. Econometrica 50: 43–61.
- Mooney, C. Z., and R. D. Duval. 1993.
- Bootstrapping: A Nonparametric Approach to Statistical Inference. Newbury Park, CA: Sage.
- Rogers, W. H. 1992.
- sg11: Quantile regression standard errors. Stata Technical Bulletin 9: 16–19. Reprinted in Stata Technical Bulletin Reprints, vol. 2, pp. 133–137.
How To Install T3 Framework
This video tutorial will guide you how to install T3 framework. There are 2 types of installation: Quickstart installation and Manual Installation.
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Now we move the project to github and you can check our project from: https://github.com/t3framework/t3
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You can select to install package (the package includes: T3 Blank Template and T3 Framework Plugin) or install one by one. The procedure includes the following steps:
Step 1: Install T3 Package
Step 2: Enable The T3 plugin
By default, when you install the plugin, it is enabled already. To check, go to: Extensions --> Plugin Manager --> find the plugin T3 Framework.
Step 3: Set T3 blank template as your default template
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Quickstart Installation
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Installation Procedure For Installing Computer In 1999 Chevy Express 3500
About T3 versions
There is always a team working on T3 Framework: support, fix bugs and develop new features. Since first stable version of T3 framework was released, there has been number of released versions. The released version comes with bug fixes, improvements and new features. You can view the information of release in T3 Framework changelog.
To have bug fixes, improvements, new features from a specific versions, you have to upgrade T3 framework to the version. But before upgrade, please always take BACKUP.
How to upgrade T3 Framework?
- Install new version of T3 Framewotk directly to your system, uninstallation is not required.
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Upgrade T3 Framework to latest version
Joomla Update
In the Template setting panel of T3 Blank template or any template developed with T3 Framework, you will se the notification if new version of template or plugin is found from the General tab
The Joomlad Update system is the override installation, so it will override all files/folder of the extension. If you have customized, so you should not use the Joomla Update system because your work will be lost.
In this case, we suggest you to use JAEM to upgrade
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We suggest to use JAEM to upgrade T3 Framework because your work will not be lost. If you use JA products, you should use JAEM for upgrading
Update JA T3v3 Framework to T3 Framework
We moved JA T3v3 to T3 project so now, we will maintain and develop T3 project instead of JA T3v3. For some templates that were developed with JA T3v3 (JA Brisk, JA Mero, JA Onepage) can be upgraded to be compatible with T3 framework.
1. Before Upgrading
BACK UP is required, please back-up your site before upgrading
There are 2 options available for your upgrading
Option 1 If you do not customize much and you can do it again
In this case, we suggest you to download Template and T3 plugin then install them again
Option 2 If you have customized a lot
Upgrade template through JAEM (JA Extension Manager) then install T3 plugin
2. Upgrade Template
To make templates compatible with T3, we had to make changes to the templates so you have to upgrade template before installing T3 plugin
Step 1: upgrade template through JAEM
To upgrade template through JAEM (JA Extension Manager Component) you need to install the component and configure it properly. Please check DETAIL GUIDEof how to use the extension.
Next, check the new version of template to upgrade
When upgrading, we only pay attention to conflicted files - files that have been modified by both User and Developer .
When upgrading, the conflicted files will be overridden by files in new version, that means what you customized in the files will be lost.
Now, upgrade template to new version. After upgrading successfully, you need to compare the conflicted files (using your back-up files) then copy what you customize to the new upgraded files.
Software Installation Procedure
3. Uninstall or Disable JA T3v3 plugin
4. Install T3 Framework Plugin
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Now, install the plugin and make sure it is enabled.
Folder Structure
Folder Structure
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T3 BS3 Blank template
T3 integrates Bootstrap, developed with LESS. Check the folder structure to know where to start.
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