| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 翁許瑋 | zh_TW |
| DC.creator | Hsu-Wei Weng | en_US |
| dc.date.accessioned | 2019-8-22T07:39:07Z | |
| dc.date.available | 2019-8-22T07:39:07Z | |
| dc.date.issued | 2019 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=106225019 | |
| dc.contributor.department | 統計研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 在本文我們指出並解決在Song et al.(2018)中的兩個問題。第一，我們描述了他們使用的半參數模型對時間尺度具有估計的不變性，並指出我們在運用Song et al.(2018)所提供的R程式套件進行估計時，結果並無具備這個性質。第二，我們發現他們的模擬設定不符合他所使用的半母數模型的假設，這可能導致模擬結果的不可靠。我們提供了一個正確的R程式碼並使用較合適的模擬設定來分析，並用以一個真實資料的例子來分析。 | zh_TW |
| dc.description.abstract | In this article we indicate and solve two issues found in Song et al.(2018). First, we characterize the time-scale invariant property of the semi-parametric model they utilize, and show that their R package provides different results after time scaling. Second, we find the setting of their main simulation does not follow the assumptions of the utilized model, which may lead to an unreliable conclusion. We provide corrected R code for practical use, and give an appropriate simulation setting to illustrate the behavior of the utilized model in a real-data example. | en_US |
| DC.subject | 增廣估計方程式 | zh_TW |
| DC.subject | 時間尺度不變性 | zh_TW |
| DC.subject | 半母數模型 | zh_TW |
| DC.subject | augmented estimating equation | en_US |
| DC.subject | time-scale invariant | en_US |
| DC.subject | semi-parametric regression | en_US |
| DC.title | New insights on ′′A semi-parametric model for wearable sensor-based physical activity monitoring data with informative device wear＂ | en_US |
| dc.language.iso | en_US | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |