Difference between revisions of "Group10 proposal"
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= Proposed Scope and Methodology = | = Proposed Scope and Methodology = | ||
− | We will confine our work to the private housing market in Singapore. This is because HDBs has many restrictions imposed and therefore to some extent, its prices are controlled. In contrast, the private housing market is open to all buyers and therefore can be more accurately determined by the attributes of the property and its surrounding. | + | We will confine our work to the private housing market in Singapore. This is because HDBs has many restrictions imposed and therefore to some extent, its prices are controlled. In contrast, the private housing market is open to all buyers and therefore can be more accurately determined by the attributes of the property and its surrounding. <br/> |
− | The surrounding amenities we will consider in our project are Schools, MRT, Bus Stops etc. | + | The surrounding amenities we will consider in our project are Schools, MRT, Bus Stops etc. <br/> |
Methodology will be linear regression and geographically weighted regression | Methodology will be linear regression and geographically weighted regression | ||
Line 44: | Line 44: | ||
= Features = | = Features = | ||
+ | Our visualisation will use the Singapore Map with the following features: <br/> | ||
+ | - Breakdown into small areas according to ??? <br/> | ||
+ | - Colour coded according to the degree of R-squared value <br/> | ||
+ | - User option to select which attributes to look at? <br/> | ||
+ | |||
+ | An example of our visualisation: <br/> | ||
[[Image:Visual_Heat_Map.jpg|1100px|frameless|center]] | [[Image:Visual_Heat_Map.jpg|1100px|frameless|center]] | ||
Revision as of 14:24, 18 March 2020
Contents
Background
Having an accurate housing price model is important for the government or policymakers as properties plays a significant role in household wealth and national economy. To date, the hedonic pricing model is still the commonly used method by researchers to study housing prices. Hedonic pricing models are often computed using an ordinary least squares (OLS) estimator, with the assumption that the observations are independent and identically distributed. This indicates that there is no spatial auto-correlation among the observations but in reality, that might not be true and thus, a hedonic pricing model could lead to biased, inconsistent and inefficient results. Our team attempts to explore the use of geographically-weighted regression (GWR) as a property pricing model and thereafter compare to see which is better. The research findings can help us understand the roles of various structural attributes and locational amenities in estimating property prices.
Motivation
Project Objectives
The objectives of the project are as follows:
1. To find out if GWR is a better estimate to private property prices in Singapore;
2. To identify the attributes that are significant in estimating property prices;
3. To understand the extent to which each attributes affect the property prices around different areas of Singapore;
4. To visually represent our findings.
Proposed Scope and Methodology
We will confine our work to the private housing market in Singapore. This is because HDBs has many restrictions imposed and therefore to some extent, its prices are controlled. In contrast, the private housing market is open to all buyers and therefore can be more accurately determined by the attributes of the property and its surrounding.
The surrounding amenities we will consider in our project are Schools, MRT, Bus Stops etc.
Methodology will be linear regression and geographically weighted regression
Project Timeline
Features
Our visualisation will use the Singapore Map with the following features:
- Breakdown into small areas according to ???
- Colour coded according to the degree of R-squared value
- User option to select which attributes to look at?
An example of our visualisation:
Data Source & Preparation
We will use 2019 REALIS data for our project.
Data Source | Documentation |
---|---|
Realis | Transaction Data of Private Property in Singapore |
School | Address of Schools |
Software
Packages
Package Name | Description |
---|---|
shiny | Building of interactive web applications |
shinydashboard | Dashboard Creation |
ShinyThemes | Themes for Shiny |
ShinyWidgets | Themes for Widgets |
Tidyverse | Collection of R packages for data analysis, packages includes ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, forcats |