hp_data

A dataset of a sample terraced houses sales in the London area for 2018 to 2024.

datasets

A framework for specifying spatially, temporally and spatially-and-temporally varying coefficient models using Generalized Additive Models with smooths. The smooths are parameterised with location, time and predictor variables. The framework supports the investigation of the presence and nature of any space-time dependencies in the data by evaluating multiple model forms (specifications) using a Generalized Cross-Validation score. The workflow sequence is to: i) Prepare the data by lengthening it to have a single location and time variables for each observation. ii) Evaluate all possible spatial and/or temporal models in which each predictor is specified in different ways. iii) Evaluate each model and pick the best one. iv) Create the final model. v) Calculate the varying coefficient estimates to quantify how the relationships between the target and predictor variables vary over space, time or space-time. vi) Create maps, time series plots etc. For more details see: Comber et al (2023) <doi:10.4230/LIPIcs.GIScience.2023.22>, Comber et al (2024) <doi:10.1080/13658816.2023.2270285> and Comber et al (2004) <doi:10.3390/ijgi13120459>.

Lex Comber

stgam

Spatially and Temporally Varying Coefficient Models Using
Generalized Additive Models

Paul Harris

Chris Brunsdon

hp_data function

A tibble with 1888 rows and 13 columns.<dl>
<dt>price</dt>
<dd>The house price in £1000s</dd><dt>priceper</dt>
<dd>The house price per square metre in £s</dd><dt>tfa</dt>
<dd>Total floor area</dd><dt>dot</dt>
<dd>Date of transfer (sale))</dd><dt>yot</dt>
<dd>Year of transfer (sale)</dd><dt>beds</dt>
<dd>Number of bedrooms</dd><dt>type</dt>
<dd>House type - here all <code>T</code> (terraced)</dd><dt>cef</dt>
<dd>Current energy efficiency rating (values from 0-100)</dd><dt>pef</dt>
<dd>Potential energy efficiency rating (values from 0-100)</dd><dt>ageb</dt>
<dd>The age band of the house constructtion</dd><dt>lad</dt>
<dd>The local authority district code of the property location</dd><dt>X</dt>
<dd>Easting in metres derived from the geometric centroid (in OSGB projecttion - EPSG 27700) of the postcode of the sale</dd><dt>Y</dt>
<dd>Northing in metres derived from the geometric centroid (in OSGB projecttion - EPSG 27700) of the postcode of the sale</dd>
</dl>

Format

London House Price dataset (Terraced, 2018-2024) — hp_data

A tibble with 1888 rows and 13 columns.<dl>
<dt>price</dt>
<dd>The house price in £1000s</dd>

<dt>priceper</dt>
<dd>The house price per square metre in £s</dd>

<dt>tfa</dt>
<dd>Total floor area</dd>

<dt>dot</dt>
<dd>Date of transfer (sale))</dd>

<dt>yot</dt>
<dd>Year of transfer (sale)</dd>

<dt>beds</dt>
<dd>Number of bedrooms</dd>

<dt>type</dt>
<dd>House type - here all <code>T</code> (terraced)</dd>

<dt>cef</dt>
<dd>Current energy efficiency rating (values from 0-100)</dd>

<dt>pef</dt>
<dd>Potential energy efficiency rating (values from 0-100)</dd>

<dt>ageb</dt>
<dd>The age band of the house constructtion</dd>

<dt>lad</dt>
<dd>The local authority district code of the property location</dd>

<dt>X</dt>
<dd>Easting in metres derived from the geometric centroid (in OSGB projecttion - EPSG 27700) of the postcode of the sale</dd>

<dt>Y</dt>
<dd>Northing in metres derived from the geometric centroid (in OSGB projecttion - EPSG 27700) of the postcode of the sale</dd>


</dl>

hp_data: London House Price dataset (Terraced, 2018-2024)

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