Bibliographic record
Abstract
The purpose of this study is to determine the significant relationship toward housing price in Malaysia from 1st Quarter 2010 to 3rd Quarter 2019. The variables that being use in this study is Interest Rates (IR), Inflation Rates (INF), Gross Domestic Product (GDP), and Money Supply (M3) as independent variables while Malaysia Housing Price Index (MHPI) as dependent variable. This paper applies Ordinary Least Square (OLS) methods in order to define the relationship among the variables. Simple Linear Regression and Multiple Linear Regression are using in order to determine the best model between dependent variable and independent variable. Empirical result shows that Multiple Linear Regression has the best model but the diagnostic test result has shows that this model has autocorrelation problem and misspecification problem. Therefore, the researcher has added a lag to the dependent variable in order to solve those problem. The result shows that interest rates, inflation rates and gross domestic product have no relationship towards housing price. Meanwhile, only money supply have positively significant relationship towards housing price.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".