Software Cost Estimation Model Based on Use Case Points by using Regression Model

Juseok, Park; Yang, Hea-Sool

doi:10.5392/jkca.2009.9.8.147

The Journal of the Korea Contents Association

2009

DOI: 10.5392/jkca.2009.9.8.147

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Software Cost Estimation Model Based on Use Case Points by using Regression Model

Park Juseok¹,

Hea-Sool Yang²

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Determination of Urban-Life Housing Price and Return Ratio by Location

Park¹,

Woo²,

Baik³

et al. 2012

The Journal of the Korea Contents Association

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The demand for small-sized housing has been increasing due to the recession of real-estate price and the increase of small-sized households. Especially, the demand for affordable housing has been increasing since the style of housing and the location fits the lifestyle of small-sized household. In addition, many investors have been buying it because it has advertised as an investment property holding high-return ratio. However, an empirical analysis about the selling price and the return ratio has not been done yet.Therefore, the purpose of the research is having the empirical analysis based on the selling price and return ration by examining the affordable housing in Seoul. The urban-life housing more than 50 generations of the Seoul was irradiated for the analysis. And the linear regression analysis and PLS(Partial Least Square Regression) analysis was used for the empirical analysis.The result of analysis, based on the linear regression analysis, showed that factors including neighboring housing price and subway catchment area have a significant effect to the determinant factors of housing price. The analysis for return ratio showed neighboring housing price, subway catchment area and amenities affects the ratio. Especially, the fault of using small sample was covered by using the partial least square regression in this research.■ keyword :|Urban-Life Housing|Sales Prices|Return Ratio|Partial Least Square Regression|

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Determination of Urban-Life Housing Price and Return Ratio by Location

Park¹,

Woo²,

Baik³

et al. 2012

The Journal of the Korea Contents Association

View full text Add to dashboard Cite

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Improving Polynomial Regression Using Principal Components Regression With the Example of the Numerical Inversion of Probability Generating Function

Yang¹,

Park²

2015

The Journal of the Korea Contents Association

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We use polynomial regression instead of linear regression if there is a nonlinear relation between a dependent variable and independent variables in a regression analysis. The performance of polynomial regression, however, may deteriorate because of the correlation caused by the power terms of independent variables. We present a polynomial regression model for the numerical inversion of PGF and show that polynomial regression results in the deterioration of the estimation of the coefficients. We apply principal components regression to the polynomial regression model and show that principal components regression dramatically improves the performance of the parameter estimation.

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Software Cost Estimation Model Based on Use Case Points by using Regression Model

Cited by 2 publications

References 1 publication

Determination of Urban-Life Housing Price and Return Ratio by Location

Determination of Urban-Life Housing Price and Return Ratio by Location

Improving Polynomial Regression Using Principal Components Regression With the Example of the Numerical Inversion of Probability Generating Function

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