TNRR : Thai National Research ระบบคลังข้อมูลงานวิจัยไทย

จำนวนงานวิจัยจำแนกรายปี

บุคคลที่เคยร่วมงานวิจัย

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บุคคลที่เคยร่วมงานวิจัย

#	นักวิจัย	ร่วมงาน
1	Sriboonchitta S.	16
2	Yamaka W.	10
3	Phochanachan P.	2
4	Boonyakunakorn P.	2
5	Sriboochitta S.	2
6	Wiboonpongse A.	1
7	Chinnakum W.	1
8	Panthamit N.	1

ปี

#	พ.ศ.	จำนวน
1	2560	8
2	2559	10
3	2556	1

ผลงานวิจัย

#	หัวเรื่อง
ปี พ.ศ. 2560
1	A generalized information theoretical approach to non-linear time series model
2	Gravity model of trade with linear quantile mixed models approach
3	Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
4	Predictive recursion maximum likelihood of threshold autoregressive model
5	Has the accumulation of foreign reserves protect the Thai economy from financial crisis?: An approach of Empirical likelihood
6	Economic growth and business cycle: The case of Thailand
7	Welfare measurement on Thai rubber market
8	Threshold regression for modeling symbolic interval data
ปี พ.ศ. 2559
9	Thailand’s export and ASEAN economic integration: A gravity model with state space approach
10	A copula-based markov switching seemingly unrelated regression approach for analysis the demand and supply on sugar market
11	Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: Dynamic copula with markov-switching
12	Effect of quantitative easing on ASEAN-5 financial markets
13	A bayesian change point with regime switching model
14	Dependence structure of and co-movement between thai currency and international currencies after introduction of quantitative easing
15	Analyzing the effect of time-varying factors for Thai rice export
16	Economic growth and income inequality: Evidence from Thailand
17	The best copula modeling of dependence structure among gold, oil prices, and U.S. currency
18	Seemingly unrelated regression based copula: An application on thai rice market
ปี พ.ศ. 2556
19	Factors affecting economic output in developed countries: A copula approach to sample selection with panel data