DSpace collection: 專書/專書篇章 http://nccur.lib.nccu.edu.tw/handle/140.119/58897 The collection's search engine Search the Channel s http://nccur.lib.nccu.edu.tw//simple-search On multivariate fuzzy time series analysis and forecasting. http://nccur.lib.nccu.edu.tw/handle/140.119/120204 title: On multivariate fuzzy time series analysis and forecasting. 在虛實之間學習：以政大書院為核心的高教實驗 http://nccur.lib.nccu.edu.tw/handle/140.119/116568 title: 在虛實之間學習：以政大書院為核心的高教實驗 abstract: 本書共分五個部分，包括「政大書院的緣起與形塑」、「主題書院的理念與實踐」、「書院教育與大學組織：通識、學務與專業教育」、「書院教育與高教發展」以及「觀察員報告」。 <br> Kolmogorov-Smirnov Two Sample Test with Continuous Fuzzy Data http://nccur.lib.nccu.edu.tw/handle/140.119/116567 title: Kolmogorov-Smirnov Two Sample Test with Continuous Fuzzy Data abstract: The Kolmogorov-Smirnov two-sample test (K-S two sample test) is a goodness-of-fit test which is used to determine whether two underlying one-dimensional probability distributions differ. In order to find the statistic pivot of a K-S two-sample test, we calculate the cumulative function by means of empirical distribution function. When we deal with fuzzy data, it is essential to know how to find the empirical distribution function for continuous fuzzy data. In our paper, we define a new function, the weight function that can be used to deal with continuous fuzzy data. Moreover we can divide samples into different classes. The cumulative function can be calculated with those divided data. The paper explains that the K-S two sample test for continuous fuzzy data can make it possible to judge whether two independent samples of continuous fuzzy data come from the same population. The results show that it is realistic and reasonable in social science research to use the K-S two-sample test for continuous fuzzy data. <br> 現代統計學 http://nccur.lib.nccu.edu.tw/handle/140.119/116566 title: 現代統計學