PCA analysis and bootstraped loadings

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PCA analysis and bootstraped loadings

Efstathia Defteraiou
Dear All,

I am relatively new in R.
Im working with the 'psych' package and 'principal' function.
I would like to know how to generate the bootstraped conf.intervals  
for loadings,
looking for sth similar to setting 'n.iter' argument for the 'fa' function.

If in 'psych' can't work and suggest me the 'boot' package please  
provide specific Rscript since I don't understand the commands and  
arguments that have to be used before calling the function 'boot'(  
what are indices? what to define as what inside function(){})

The names Im using are included in the following code:
'newdata3.1' is my data and provided as data.frame

makingtheanalysis3.1 <-principal(newdata3.1, nfactors =3,
                               residuals = FALSE,
                               covar=FALSE,rotate="varimax",scores=TRUE)


I am sorry for not providing a specific code but my data are too large

Any Help appreciated
Cheers!

______________________________________________
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Re: PCA analysis and bootstraped loadings

ssefick
Hi,

Please search the mailing list archives for this, or type bootstrapped PCA
R into google. Please provide a minimal self-contained example of what you
are trying to solve. Please read the posting guide that is referenced at
the end of every email.
kind regards,

Stephen

On Mon, Apr 13, 2015 at 11:07 AM, Efstathia Defteraiou <
[hidden email]> wrote:

> Dear All,
>
> I am relatively new in R.
> Im working with the 'psych' package and 'principal' function.
> I would like to know how to generate the bootstraped conf.intervals for
> loadings,
> looking for sth similar to setting 'n.iter' argument for the 'fa' function.
>
> If in 'psych' can't work and suggest me the 'boot' package please provide
> specific Rscript since I don't understand the commands and arguments that
> have to be used before calling the function 'boot'( what are indices? what
> to define as what inside function(){})
>
> The names Im using are included in the following code:
> 'newdata3.1' is my data and provided as data.frame
>
> makingtheanalysis3.1 <-principal(newdata3.1, nfactors =3,
>                               residuals = FALSE,
>                               covar=FALSE,rotate="varimax",scores=TRUE)
>
>
> I am sorry for not providing a specific code but my data are too large
>
> Any Help appreciated
> Cheers!
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/
> posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



--
Stephen Sefick
**************************************************
Auburn University
Biological Sciences
331 Funchess Hall
Auburn, Alabama
36849
**************************************************
[hidden email]
http://www.auburn.edu/~sas0025
**************************************************

Let's not spend our time and resources thinking about things that are so
little or so large that all they really do for us is puff us up and make us
feel like gods.  We are mammals, and have not exhausted the annoying little
problems of being mammals.

                                -K. Mullis

"A big computer, a complex algorithm and a long time does not equal
science."

                              -Robert Gentleman

        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: PCA analysis and bootstraped loadings

William Revelle
psych does not currently have bootstrapped confidence intervals for loadings.  That is a reasonable request and I will try to add it, perhaps in the “real soon now” version of 1.5.4 (almost finished), perhaps in the next release,

Bill

> On Apr 13, 2015, at 2:38 PM, stephen sefick <[hidden email]> wrote:
>
> Hi,
>
> Please search the mailing list archives for this, or type bootstrapped PCA
> R into google. Please provide a minimal self-contained example of what you
> are trying to solve. Please read the posting guide that is referenced at
> the end of every email.
> kind regards,
>
> Stephen
>
> On Mon, Apr 13, 2015 at 11:07 AM, Efstathia Defteraiou <
> [hidden email]> wrote:
>
>> Dear All,
>>
>> I am relatively new in R.
>> Im working with the 'psych' package and 'principal' function.
>> I would like to know how to generate the bootstraped conf.intervals for
>> loadings,
>> looking for sth similar to setting 'n.iter' argument for the 'fa' function.
>>
>> If in 'psych' can't work and suggest me the 'boot' package please provide
>> specific Rscript since I don't understand the commands and arguments that
>> have to be used before calling the function 'boot'( what are indices? what
>> to define as what inside function(){})
>>
>> The names Im using are included in the following code:
>> 'newdata3.1' is my data and provided as data.frame
>>
>> makingtheanalysis3.1 <-principal(newdata3.1, nfactors =3,
>>                              residuals = FALSE,
>>                              covar=FALSE,rotate="varimax",scores=TRUE)
>>
>>
>> I am sorry for not providing a specific code but my data are too large
>>
>> Any Help appreciated
>> Cheers!
>>
>> ______________________________________________
>> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/
>> posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
>
> --
> Stephen Sefick
> **************************************************
> Auburn University
> Biological Sciences
> 331 Funchess Hall
> Auburn, Alabama
> 36849
> **************************************************
> [hidden email]
> http://www.auburn.edu/~sas0025
> **************************************************
>
> Let's not spend our time and resources thinking about things that are so
> little or so large that all they really do for us is puff us up and make us
> feel like gods.  We are mammals, and have not exhausted the annoying little
> problems of being mammals.
>
>                                -K. Mullis
>
> "A big computer, a complex algorithm and a long time does not equal
> science."
>
>                              -Robert Gentleman
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

William Revelle           http://personality-project.org/revelle.html
Professor           http://personality-project.org
Department of Psychology   http://www.wcas.northwestern.edu/psych/
Northwestern University   http://www.northwestern.edu/
Use R for psychology             http://personality-project.org/r
It is 3 minutes to midnight   http://www.thebulletin.org

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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Re: PCA analysis and bootstraped loadings

Efstathia Defteraiou
Dear All,
Thank You for the quick responses.
Managed to solve my problem through:
http://www.faculty.biol.ttu.edu/strauss/multivar/R/SamplePCABootstrap.R.txt
or
http://r.789695.n4.nabble.com/bootstrapped-eigenvector-method-following-prcomp-td877655.html
Used the first one however, code is too long since everything is  
manually done.
The suggestion of Bill would be very kind and save a lot of time in  
the future.
Thanks William for clearing this up.

Cheers
Efi


Zitat von William Revelle <[hidden email]>:

> psych does not currently have bootstrapped confidence intervals for  
> loadings.  That is a reasonable request and I will try to add it,  
> perhaps in the “real soon now” version of 1.5.4 (almost finished),  
> perhaps in the next release,
>
> Bill
>
>> On Apr 13, 2015, at 2:38 PM, stephen sefick <[hidden email]> wrote:
>>
>> Hi,
>>
>> Please search the mailing list archives for this, or type bootstrapped PCA
>> R into google. Please provide a minimal self-contained example of what you
>> are trying to solve. Please read the posting guide that is referenced at
>> the end of every email.
>> kind regards,
>>
>> Stephen
>>
>> On Mon, Apr 13, 2015 at 11:07 AM, Efstathia Defteraiou <
>> [hidden email]> wrote:
>>
>>> Dear All,
>>>
>>> I am relatively new in R.
>>> Im working with the 'psych' package and 'principal' function.
>>> I would like to know how to generate the bootstraped conf.intervals for
>>> loadings,
>>> looking for sth similar to setting 'n.iter' argument for the 'fa' function.
>>>
>>> If in 'psych' can't work and suggest me the 'boot' package please provide
>>> specific Rscript since I don't understand the commands and arguments that
>>> have to be used before calling the function 'boot'( what are indices? what
>>> to define as what inside function(){})
>>>
>>> The names Im using are included in the following code:
>>> 'newdata3.1' is my data and provided as data.frame
>>>
>>> makingtheanalysis3.1 <-principal(newdata3.1, nfactors =3,
>>>                              residuals = FALSE,
>>>                              covar=FALSE,rotate="varimax",scores=TRUE)
>>>
>>>
>>> I am sorry for not providing a specific code but my data are too large
>>>
>>> Any Help appreciated
>>> Cheers!
>>>
>>> ______________________________________________
>>> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/
>>> posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>>
>>
>> --
>> Stephen Sefick
>> **************************************************
>> Auburn University
>> Biological Sciences
>> 331 Funchess Hall
>> Auburn, Alabama
>> 36849
>> **************************************************
>> [hidden email]
>> http://www.auburn.edu/~sas0025
>> **************************************************
>>
>> Let's not spend our time and resources thinking about things that are so
>> little or so large that all they really do for us is puff us up and make us
>> feel like gods.  We are mammals, and have not exhausted the annoying little
>> problems of being mammals.
>>
>>                                -K. Mullis
>>
>> "A big computer, a complex algorithm and a long time does not equal
>> science."
>>
>>                              -Robert Gentleman
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> William Revelle           http://personality-project.org/revelle.html
> Professor           http://personality-project.org
> Department of Psychology   http://www.wcas.northwestern.edu/psych/
> Northwestern University   http://www.northwestern.edu/
> Use R for psychology             http://personality-project.org/r
> It is 3 minutes to midnight   http://www.thebulletin.org
>
>
>
>
>
>
>

______________________________________________
[hidden email] mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.