Re: [R] Fitting Arima Model to Daily Time Series

2013-09-11 Thread Jose Iparraguirre
Paul
Good you ask because as far as I can remember (some people in the forum are 
experts on both time series and how R handles time series), it's not advisable 
to use the ts() function in the base package when dealing with daily 
observations (because of leap years, mostly).

Therefore, you need to use the packages zoo or xts, as explained here:  
http://stackoverflow.com/questions/8437620/analyzing-daily-weekly-data-using-ts-in-r
 
You can also use the package timeSeries. If you need to take into account 
weekdays or weekends (that depends on your research question and modelling, of 
course), R can do it for you as well.

Best,

José




From: Paul Bernal [mailto:paulberna...@gmail.com] 
Sent: 11 September 2013 15:41
To: Jose Iparraguirre
Cc: r-help@r-project.org
Subject: Re: [R] Fitting Arima Model to Daily Time Series

Dear Jose, good morning,

First of all, let me thank you for your extremely valuable help. Now I have a 
question for you:

I have a table containing two fields, the first one is date and the second one 
is number of transits of vessels. This table contains daily observations for 
the past 5 years.

The date field has the following format: -MM-DD

The number of transits field is a regular numeric field.

How can I do to convert this table into a time series object?

Best regards,

Paul



2013/9/11 Jose Iparraguirre 
Hi Paul,

There are different packages in R to fit an ARIMA model. I would use the 
forecast package.
In your case, perhaps you would want to explore SARIMA models to include 
seasonal components?
Anyhow, the first port of call could be the auto.arima() function to select the 
best fitting representation according to AIC, AICc or BIC -but explore other 
representations as well.
To fit the models use the function Arima (note the capital "A"). The 
documentation in the package is very clear and comprehensive; the authors (Rob 
J Hyndman and George Athanasopoulos) published a free on-line book which will 
also help you: http://otexts.com/fpp/.
Hope this helps,

José


Prof. José Iparraguirre
Chief Economist
Age UK



-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
Behalf Of Paul Bernal
Sent: 10 September 2013 22:54
To: r-help@r-project.org
Subject: [R] Fitting Arima Model to Daily Time Series

Hello everyone,

Hope everyone is doing great. I would like to know how to use the arima 
function in R to fit arima or arma models to daily data, that is, with period = 
365, this taking into account the fact that I have 5 years worth of daily data 
(so 365 * 5 = my number of observations).

All I want is a very general line of code of I I would do to fit the arima 
model.

Any help will be greatly appreciated,

Have a wonderful day,

Paul
        [[alternative HTML version deleted]]

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Re: [R] Fitting Arima Model to Daily Time Series

2013-09-11 Thread Paul Bernal
Dear Jose, good morning,

First of all, let me thank you for your extremely valuable help. Now I have
a question for you:

I have a table containing two fields, the first one is date and the second
one is number of transits of vessels. This table contains daily
observations for the past 5 years.

The date field has the following format: -MM-DD

The number of transits field is a regular numeric field.

How can I do to convert this table into a time series object?

Best regards,

Paul




2013/9/11 Jose Iparraguirre 

> Hi Paul,
>
> There are different packages in R to fit an ARIMA model. I would use the
> forecast package.
> In your case, perhaps you would want to explore SARIMA models to include
> seasonal components?
> Anyhow, the first port of call could be the auto.arima() function to
> select the best fitting representation according to AIC, AICc or BIC -but
> explore other representations as well.
> To fit the models use the function Arima (note the capital "A"). The
> documentation in the package is very clear and comprehensive; the authors
> (Rob J Hyndman and George Athanasopoulos) published a free on-line book
> which will also help you: http://otexts.com/fpp/.
> Hope this helps,
>
> José
>
>
> Prof. José Iparraguirre
> Chief Economist
> Age UK
>
>
>
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Paul Bernal
> Sent: 10 September 2013 22:54
> To: r-help@r-project.org
> Subject: [R] Fitting Arima Model to Daily Time Series
>
> Hello everyone,
>
> Hope everyone is doing great. I would like to know how to use the arima
> function in R to fit arima or arma models to daily data, that is, with
> period = 365, this taking into account the fact that I have 5 years worth
> of daily data (so 365 * 5 = my number of observations).
>
> All I want is a very general line of code of I I would do to fit the arima
> model.
>
> Any help will be greatly appreciated,
>
> Have a wonderful day,
>
> Paul
>
> [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> 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.
>
> The Wireless from Age UK | Radio for grown-ups.
>
> www.ageuk.org.uk/thewireless
>
>
> If you’re looking for a radio station that offers real variety, tune in to
> The Wireless from Age UK.
> Whether you choose to listen through the website at
> www.ageuk.org.uk/thewireless, on digital radio (currently available in
> London and Yorkshire) or through our TuneIn Radio app, you can look forward
> to an inspiring mix of music, conversation and useful information 24 hours
> a day.
>
>
>
>
> ---
> Age UK is a registered charity and company limited by guarantee,
> (registered charity number 1128267, registered company number 6825798).
> Registered office: Tavis House, 1-6 Tavistock Square, London WC1H 9NA.
>
> For the purposes of promoting Age UK Insurance, Age UK is an Appointed
> Representative of Age UK Enterprises Limited, Age UK is an Introducer
> Appointed Representative of JLT Benefit Solutions Limited and Simplyhealth
> Access for the purposes of introducing potential annuity and health
> cash plans customers respectively.  Age UK Enterprises Limited, JLT
> Benefit Solutions Limited and Simplyhealth Access are all authorised and
> regulated by the Financial Services Authority.
> --
>
> This email and any files transmitted with it are confidential and intended
> solely for the use of the individual or entity to whom they are
> addressed. If you receive a message in error, please advise the sender and
> delete immediately.
>
> Except where this email is sent in the usual course of our business, any
> opinions expressed in this email are those of the author and do not
> necessarily reflect the opinions of Age UK or its subsidiaries and
> associated companies. Age UK monitors all e-mail transmissions passing
> through its network and may block or modify mails which are deemed to be
> unsuitable.
>
> Age Concern England (charity number 261794) and Help the Aged (charity
> number 272786) and their trading and other associated companies merged
> on 1st April 2009.  Together they have formed the Age UK Group, dedicated
> to improving the lives of people in later life.  The three national
> Age Concerns in Scotland, Northern Ireland and Wales have also merged with
> Help the Aged in these nations to form three registered charities:
> Age Scotland, 

Re: [R] Fitting Arima Model to Daily Time Series

2013-09-11 Thread Jose Iparraguirre
Hi Paul,

There are different packages in R to fit an ARIMA model. I would use the 
forecast package.
In your case, perhaps you would want to explore SARIMA models to include 
seasonal components? 
Anyhow, the first port of call could be the auto.arima() function to select the 
best fitting representation according to AIC, AICc or BIC -but explore other 
representations as well.
To fit the models use the function Arima (note the capital "A"). The 
documentation in the package is very clear and comprehensive; the authors (Rob 
J Hyndman and George Athanasopoulos) published a free on-line book which will 
also help you: http://otexts.com/fpp/.
Hope this helps,

José


Prof. José Iparraguirre
Chief Economist
Age UK



-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On 
Behalf Of Paul Bernal
Sent: 10 September 2013 22:54
To: r-help@r-project.org
Subject: [R] Fitting Arima Model to Daily Time Series

Hello everyone,

Hope everyone is doing great. I would like to know how to use the arima 
function in R to fit arima or arma models to daily data, that is, with period = 
365, this taking into account the fact that I have 5 years worth of daily data 
(so 365 * 5 = my number of observations).

All I want is a very general line of code of I I would do to fit the arima 
model.

Any help will be greatly appreciated,

Have a wonderful day,

Paul

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
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.

The Wireless from Age UK | Radio for grown-ups.

www.ageuk.org.uk/thewireless


If you’re looking for a radio station that offers real variety, tune in to The 
Wireless from Age UK. 
Whether you choose to listen through the website at 
www.ageuk.org.uk/thewireless, on digital radio (currently available in London 
and Yorkshire) or through our TuneIn Radio app, you can look forward to an 
inspiring mix of music, conversation and useful information 24 hours a day.



 
---
Age UK is a registered charity and company limited by guarantee, (registered 
charity number 1128267, registered company number 6825798). 
Registered office: Tavis House, 1-6 Tavistock Square, London WC1H 9NA.

For the purposes of promoting Age UK Insurance, Age UK is an Appointed 
Representative of Age UK Enterprises Limited, Age UK is an Introducer 
Appointed Representative of JLT Benefit Solutions Limited and Simplyhealth 
Access for the purposes of introducing potential annuity and health 
cash plans customers respectively.  Age UK Enterprises Limited, JLT Benefit 
Solutions Limited and Simplyhealth Access are all authorised and 
regulated by the Financial Services Authority. 
--

This email and any files transmitted with it are confidential and intended 
solely for the use of the individual or entity to whom they are 
addressed. If you receive a message in error, please advise the sender and 
delete immediately.

Except where this email is sent in the usual course of our business, any 
opinions expressed in this email are those of the author and do not 
necessarily reflect the opinions of Age UK or its subsidiaries and associated 
companies. Age UK monitors all e-mail transmissions passing 
through its network and may block or modify mails which are deemed to be 
unsuitable.

Age Concern England (charity number 261794) and Help the Aged (charity number 
272786) and their trading and other associated companies merged 
on 1st April 2009.  Together they have formed the Age UK Group, dedicated to 
improving the lives of people in later life.  The three national 
Age Concerns in Scotland, Northern Ireland and Wales have also merged with Help 
the Aged in these nations to form three registered charities: 
Age Scotland, Age NI, Age Cymru.




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[R] Fitting Arima Model to Daily Time Series

2013-09-10 Thread Paul Bernal
Hello everyone,

Hope everyone is doing great. I would like to know how to use the arima
function in R to fit arima or arma models to daily data, that is, with
period = 365, this taking into account the fact that I have 5 years worth
of daily data (so 365 * 5 = my number of observations).

All I want is a very general line of code of I I would do to fit the arima
model.

Any help will be greatly appreciated,

Have a wonderful day,

Paul

[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list
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.