I have climate data (temperature, precipitation, snow depth) for all of Canada between 1900 and 2009. I have written a basic website and the simplest page allows users to choose category and city. They then get back a very simple report (without the parameters and calculations section):
The primary purpose of the web application is to provide a simple user interface so that the general public can explore the data in meaningful ways. (A list of numbers is not meaningful to the general public, nor is a website that provides too many inputs.) The secondary purpose of the application is to provide climatologists and other scientists with deeper ways to view the data. (Using too many inputs, of course.)
The database is PostgreSQL with R (mostly) installed. The reports are written using iReport and generated using JasperReports.
Currently, a linear regression model is applied against annual averages of daily data. The linear regression model is calculated within a PostgreSQL function as follows:
SELECT
regr_slope( amount, year_taken ),
regr_intercept( amount, year_taken ),
corr( amount, year_taken )
FROM
temp_regression
INTO STRICT slope, intercept, correlation;
The results are returned to JasperReports using:
SELECT
year_taken,
amount,
year_taken * slope + intercept,
slope,
intercept,
correlation,
total_measurements
INTO result;
JasperReports calls into PostgreSQL using the following parameterized analysis function:
SELECT
year_taken,
amount,
measurements,
regression_line,
slope,
intercept,
correlation,
total_measurements,
execute_time
FROM
climate.analysis(
$P{CityId},
$P{Elevation1},
$P{Elevation2},
$P{Radius},
$P{CategoryId},
$P{Year1},
$P{Year2}
)
ORDER BY year_taken
This is not an optimal solution because it gives the false impression that the climate is changing at a slow, but steady rate.
Using functions that take two parameters (e.g., year [X] and amount [Y]), such as PostgreSQL's regr_slope
:
apt-get
.)If no such functions exist:
Keep in mind that this is a web app for use by the general public. If the only way to analyse the data is from an R shell, then the purpose has been defeated. (I know this is not the case for most R functions I have looked at so far.)
Thank you!
The awesome pl/r package allows you to run R inside PostgreSQL as a procedural language. There are some gotchas because R likes to think about data in terms of vectors which is not what a RDBMS does. It is still a very useful package as it gives you R inside of PostgreSQL saving you some of the roundtrips of your architecture.
And pl/r is apt-get
-able for you as it has been part of Debian / Ubuntu for a while. Start with apt-cache show postgresql-8.4-plr
(that is on testing, other versions/flavours have it too).
As for the appropriate modeling: that is a whole different ballgame. loess
is a fair suggestion for something non-parametric, and you probably also want some sort of dynamic model, either ARMA/ARIMA or lagged regression. The choice of modeling is pretty critical given how politicized the topic is.