This is about my experience. I hope to let everyone know me better.

Introduction

At the beginning of my teaching and research stage, I began to apply economic theories to the phenomena of financial market and industrial structure. Until 2012, I met the research bottleneck and returned to basic research. The first difficulty in the research is the test method of the Durbin-Watson statistic, which I have always doubted is different from other test statistics. This is also a problem that has always existed in financial data.

Through the simulation of the probability distribution simulator and the deconstruction of Durbin-Watson statistic, I found that this method can make the economic models as a “real” random and dynamic result, and then I published several papers on the random and dynamic game theory. Of course, this is not enough to solve the economic and financial phenomena that I want to know. I need precise modeling techniques, because economic models need to find mathematical models. After 2016, the whole research method would be completed step by step. This research method includes knowledge and technology of data simulation, probability model, statistical model, estimation model and variable transformation. This convinced me that the data-driven models can be found by the accurately estimation, and can also be generated the simulated data to verify the exaction of the theoritical or data model.

I have the copyright of all the above knowledge and technology.

You can learn relevant knowledge and technology from the works by my co-authors and me.

• There are five books published. Three books are in English, and two book is in traditional Chinese.
• The research method used in the journal papers are also derived from the above-mentioned knowledge and techniques.

Publishions

Books (in total of 9)

• Demythologize Durbin-Watson test statistic, 2022, Amazon.com.

• Excel calucluating probablity distribution simulator, 2021, Amazon.com.

• Special Beta Distribution for Big Data Analysis: X ~ Beta(α = λ + 1, β = 2 -λ), 2021, vixra.

• Multi Categories Analytic Method Using Continuous Bernoulli Distribution and Conditional Distribution, 2021, vixra.

• The Continuous Bernoulli Approaching Distribution When λ → 0 and the Continuous Binomial Distribution, 2020, vixra.

• Continuous Bernoulli Distribution-Simulator and Test Statistic, 2020, vixra,free-ebook.net.

• Statistics cannot be the tool of big data analysis: reasons and corrections, 2019, books.com.tw. (Traditional Chinese version)

• The formula of big data using Statistics: all probability distributions used, 2016, e-book.(Traditional Chinese version)

• Big Data Analysis Method, 2015, e-book.

• Big Data Analysis Method, 2015, Pubu. (Traditional Chinese version)

Journal papers in the recent five years

• Ya-Chuan Chan, Yao-Hsien Lee$^{*}$, Mei-Yu Lee, 2021, Stock Market behaviors among US, China and Taiwan, Journal of Accounting, Finance & Management Strategy, 16(2), 109-136. (EconLit)

• Ya-Chuan Chan, Yao-Hsien Lee$^{*}$, Mei-Yu Lee, 2021, Does COVID-19 Change the Relationship among Taiwan Stock Index Futures, MSCI Morgan Taiwan Index, and Taiwan Stock Price Index?, Expert Journal of Economics, 9(1), 18-33. (EconLit)

• Chih-Wen Hsiao, Ya-Chuan Chan$^{*}$, Mei-Yu Lee, Hsi-Peng Lu, 2021, Heteroscedasticity and Precise Estimation Model Approach for Complex Financial Time-Series Data: An Example of Taiwan Stock Index Futures before and during COVID-19, Mathematics, 9(21), 2719. (SCIE, IF=2.258, SCOPUS=2.2)

• 李玫郁、孔秀琴、呂英瑞，2020，「運用大數據分析方法估計失業人數與失業率」，台灣銀行季刊，第71卷第1期，第49-70頁。

• 李玫郁，2018，「大數據分析方法現況與可行之道 」，台灣銀行季刊，第69卷第3期，第205頁。

• 鄭貴元、李堯賢、李玫郁，2017，「對外貿易和中國崛起對台灣實質薪資型菲利浦曲線之影響分析」，育達科大學報，第45期，第1-14頁。

• Yao-Hsien Lee, Yi-Hsien Wang and Mei-Yu Lee, 2017, Big data analysis of foreign exchange rates among Japan, South Korea and Taiwan, *International Journal of Computational Economics and Econometrics, 7(4), 399-410.

• 邱登裕、端木和奕、謝素真、李玫郁*，2016，「以多重彈性倒傳遞類神經模型探討台灣4G概念股股價的變動」，會計與財金研究，第9卷第1期，第51-66頁。

• Kuei-Yuan Cheng, Yao-Hsien Lee and Mei-Yu Lee, 2016, Price Competition between Shrink-wrap Software and Cloud Service Firms under a Stochastic Model, *Problems and Perspectives in Management, 14(2), 272-276. (EconLit, IF = 0.765)

• 李玫郁、李堯賢、林哲揚，2016，「國際油價與中油油品價格之大數據特徵分析」，台灣銀行季刊，67(2)，第53-78頁。

• Mei-Yu Lee, 2016, On the DurbinWatson Statistic Based on a Z-Test in Large Samples, International Journal of Computational Economics and Econometrics, 6(1), 114-121. (IF = 0.3)

Research projects

Seek the job or cooperation from university, research center or others. Please feel free to contact me.

Central limit theorem of 28 probability distributions using the probability distribution simulator

Some cases has been published on YouTube. Video is better to show the results because there are too many results for each case and this needs to exhibit the Central Limit Theorem property.

• Case 1,The population distribution~Normal distribution
• Case 2, The population distribution~ Uniform distribution
• Case 3, The population distribution ~ Shifted exponential distribution
• Case 4, The population distribution~ Pareto 1 distribution
• Case 5, The population distribution~ Arcsin distribution
• Case 6, The population distribution~ Bernoulli distribution (one population proportion)
• Case 7, The population distribution~ Rayleigh distribution
• Case 8, The population distribution~ Gumbel distribution
• Case 9, The population distribution~ Logistic distribution
• Case 10, The population distribution~ Weibull distribution
• Case 11, The population distribution ~ Pareto 2 distribution
• Case 12, The population distribution ~ Pareto 3 distribution
• Case 13, The population distribution ~ Triangular 2 distribution
• Case 14, The population distribution ~ Triangular 3 distribution
• Case 15, The population distribution ~ Log logistic distribution
• Case 16, The population distribution ~ Hyperbolic secant distribution
• Case 17, The population distribution ~ Kumaraswamy distribution
• Case 18, The population distribution ~ Gumbel(type 1) distribution
• Case 19, The population distribution ~ Gumbel(type 2) distribution
• Case 20, The population distribution ~ Double exponential distribution
• Case 21, The population distribution ~ Continuous Bernoulli distribution
• Case 22, The population distribution ~ Generalized logistic distribution type I
• Case 23, The population distribution ~ Exponential logarithmic distribution
• Case 24, The population distribution ~ Dagum distribution
• Case 25, The population distribution ~ Gompertz distribution
• Case 26, The population distribution ~ U quadratic distribution
• Case 27, The population distribution ~ Semicircle distribution
• Case 28, The population distribution ~ Discrete Uniform distribution

Economic applications using the probability distribution simulator

• Demand-supply model
• consumer theory
• firm theory
• game theory

Accurate data-driven model building

• Economic data
• Financial data
• Sales data
• Crime data

Teaching of Probablity distribution simulator

academic, education, programming, certificate

Basic:

• Part 1: Introduce the random variable, probaiblity, probabilty distribution, sampling distribution
• Part 2: Simulate the probabiltiy distribution of one random variable
• Part 3: Simulate the probability distribution of function of one random variable (with comparsion)

Intermediate:

• Part 4: Simulate the probabiltiy distribution of two indepedent random variables
• Part 5: Simulate the probability distributoin of function of two indepedent random variables
• Part 6: Simulate the probability distribution of two dependent random variables
• Part 7: Simulate the probability distribution of function of two dependent random variables
• Part 8: Simulate the probabiltiy distribuition of three or more independent random variables

Advanced:

• Part 9: Design probability models
• Part 10: Design statistic models

Teaching of decision for AI analaysis (Bayesian theorem method)

• Introduce the probability: marignal probability, joint probability, conditional probability
• How to calculate the frequency of the text data
• How to calculate the frequency of the number data
• How to run the software to find the regularities of data on the criterion of the maximum probability, minimum probability, the median, the average.
• Interprete data results.