Dixon, Conor (2014) Time Series Forecasting of Residential House Sale Prices in Dublin for 2014. Diploma thesis, Dublin, National College of Ireland.
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How can accurate time series modelling and forecasting of residential house prices be achieved. Univariate time series decomposition, modelling and forecasting of residential house sale price time series is implemented covering the period 2010 – 2013. The house sale price series dataset was sourced from the Property Services Regulatory Authority – Residential Property Price Register (PPR). Three univariate models implemented; a moving average time series decomposition, exponential smoothing state space model and autoregressive integrated moving average model. The time series modelling, point and interval forecasts and prediction intervals are automated by the R programming language forecast package functions. The Box-Ljung test of exponential smoothing state space model and ARIMA model residuals produce X-squared = 0.3426, df = 1, p-value = 0.5583. The test results highlight the null hypothesis that the data is independently distributed cannot be rejected.
|Item Type:||Thesis (Diploma)|
|Subjects:||Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
|Divisions:||School of Computing > Higher Diploma in Science in Data Analytics|
|Depositing User:||CAOIMHE NI MHAICIN|
|Date Deposited:||12 Dec 2014 16:32|
|Last Modified:||12 Dec 2014 16:32|
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