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康尧，博士

副教授，硕导(学硕，专硕)

西安交通大学，数学与统计学院，统计与数据科学系

陕西省西安市咸宁西路28号，邮编：710049

邮箱：kangyao92@163.com

           kangyao92@xjtu.edu.cn

康尧，博士，西安交通大学副教授，硕士生导师，2020年6月于吉林大学获得博士学位，2020年7月进入西安交通大学数学与统计学院工作。目前主要从事时间序列分析、统计过程控制和保险精算等方面的研究，以第一作者和通讯作者身份于TEST、The Canadian Journal of Statistics和Economics Letters等统计学和经济学期刊发表SCI/SSCI论文16篇，先后主持国家自然科学基金青年项目、国家社会科学基金青年项目、中国博士后国资计划项目和中国博士后面上项目等7项，担任中国现场统计研究会大数据统计分会、中国现场统计研究会贝叶斯统计分会理事，担任Applied Mathematical Modelling、Statistical Papers、Journal of Statistical Computation and Simulation、Methodology and Computing in Applied Probability、Environmental and Ecological Statistics和Journal of Systems Science and Complexity等期刊的匿名审稿人。

工作经历：2024.07-至今，西安交通大学，副教授 ，硕导；

                   2020.07-2024.07，西安交通大学，助理教授

授课情况：《概率论》，《时间序列与金融统计》，《数理统计》

研究领域：时间序列分析，保险精算，统计过程控制

科研项目：主持国家级项目2项，省部级项目3项，校级项目2项

论文发表：(*表示通讯作者)

[1] Yao Kang, Junrong Song, Yuteng Zhang, Yongchang Hui*. (2025). Modelling ℤ-valued time series with Skellam thinning-based INAR(1) process. Applied Economics, accepted. 

[2] Yao Kang, Yuqing Zhang, Shuhui Wang*, Zhiwen Zhao. (2025). A new class of ℤ-valued INAR(1) models with application to mutual fund flows. Economics Letters, 252, 112339.  

[3] Yao Kang, Xiaojing Fan, Jie Zhang*, Ying Tang. (2025). Modeling and testing for endpoint-inflated count time series with bounded support. Journal of Statistical Planning and Inference, 237, 106248.

[4] Yao Kang, Yuqing Zhang, Feilong Lu, Danshu Sheng, Shuhui Wang*, Chang Liu. (2025). A signed binomial autoregressive model for the bounded ℤ-valued time series. Journal of Statistical Computation and Simulation, 95(8), 1735–1762.

[5] Yao Kang, Danshu Sheng, Feilong Lu*. (2025). A simple INAR(1) model for analyzing count time series with multiple features. Communications in Statistics-Theory and Methods, 54(2), 457–475.

[6] Yao Kang, Danshu Sheng*, Jinmei Yue. (2024). Threshold integer-valued autoregressive model with serially dependent innovation. Journal of Statistical Computation and Simulation, 94(17), 3826–3863.

[7] Danshu Sheng, Chang Liu, Yao Kang*. (2024). Change-point analysis for binomial autoregressive model with application to price stability counts. Journal of Computational and Applied Mathematics, 451, 116079.

[8] Yao Kang, Feilong Lu*, Shuhui Wang. (2024). Bayesian analysis for an improved mixture binomial autoregressive model with applications to rainy-days and air quality level data. Stochastic Environmental Research and Risk Assessment, 38, 1313–1333.

[9] Yao Kang, Fukang Zhu*, Dehui Wang, Shuhui Wang. (2024). A zero-modified geometric INAR(1) model for analyzing count time series with multiple features. The Canadian Journal of Statistics, 52(3), 873–899.

[10] Yao Kang, Feilong Lu, Danshu Sheng, Shuhui Wang*. (2024). A seasonal binomial autoregressive process with applications to monthly rainy-days counts. Stochastic Environmental Research and Risk Assessment, 38, 2859–2873.

[11] Danshu Sheng, Dehui Wang*, Yao Kang. (2024). A new RCAR(1) model based on explanatory variables and observations. Communications in Statistics-Theory and Methods, 53(7), 2285–2306.

[12] Yao Kang, Shuhui Wang, Dehui Wang, Fukang Zhu*. (2023). Analysis of zero-and-one inflated bounded count time series with applications to climate and crime data. TEST, 32, 34–73.

[13] Yao Kang, Dehui Wang, Feilong Lu, Shuhui Wang*. (2022). Flexible INAR(1) models for equidispersed, underdispersed or overdispersed counts. Journal of the Korean Statistical Society, 51, 1268–1301.

[14] Yao Kang, Dehui Wang*, Kai Yang. (2021). A new INAR(1) process with bounded support for counts showing equidispersion, underdispersion and overdispersion. Statistical Papers, 62, 745–767.

[15] Yao Kang, Dehui Wang*, Jianhua Cheng. (2021). Risk models based on copulas for premiums and claim sizes. Communications in Statistics-Theory and Methods,  50, 2250–2269. 

[16] Yao Kang, Dehui Wang*, Kai Yang, Yulin Zhang. (2020).A new thinning-based INAR(1) process for underdispersed or overdispersed counts. Journal of the Korean Statistical Society, 49, 324–349.

[17] Yao Kang, Dehui Wang*, Kai Yang. (2020). Extended binomial AR(1) processes with generalized binomial thinning operator, Communications in Statistics-Theory and Methods, 49(14), 3498–3520.

[18] Kai Yang, Yao Kang, Dehui Wang*, Han Li, Yajing Diao. (2019). Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued autoregressive processes. Metrika, 82, 863–889.