派博傳思國際中心

標(biāo)題: Titlebook: Copula-Based Markov Models for Time Series; Parametric Inference Li-Hsien Sun,Xin-Wei Huang,Takeshi Emura Book 2020 The Editor(s) (if appli [打印本頁]

作者: VEER    時(shí)間: 2025-3-21 17:46
書目名稱Copula-Based Markov Models for Time Series影響因子(影響力)




書目名稱Copula-Based Markov Models for Time Series影響因子(影響力)學(xué)科排名




書目名稱Copula-Based Markov Models for Time Series網(wǎng)絡(luò)公開度




書目名稱Copula-Based Markov Models for Time Series網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Copula-Based Markov Models for Time Series被引頻次




書目名稱Copula-Based Markov Models for Time Series被引頻次學(xué)科排名




書目名稱Copula-Based Markov Models for Time Series年度引用




書目名稱Copula-Based Markov Models for Time Series年度引用學(xué)科排名




書目名稱Copula-Based Markov Models for Time Series讀者反饋




書目名稱Copula-Based Markov Models for Time Series讀者反饋學(xué)科排名





作者: 繁重    時(shí)間: 2025-3-21 20:29

作者: 健談    時(shí)間: 2025-3-22 03:34

作者: 一大群    時(shí)間: 2025-3-22 04:42
Estimation Under Normal Mixture Models for Financial Time Series Data,assets, we select a normal mixture distribution for the marginal distribution. Based on the normal mixture distribution for the marginal distribution and the Clayton copula for serial dependence, we obtain the corresponding likelihood function. In order to obtain the maximum likelihood estimators, w
作者: gusher    時(shí)間: 2025-3-22 10:04
Bayesian Estimation Under the ,-Distribution for Financial Time Series,rkov chain. Due to the computational difficulty of obtaining maximum likelihood estimates, alternatively, we develop Bayesian inference using the empirical Bayes method through the resampling procedure. We provide a Metropolis–Hastings algorithm to simulate the posterior distribution. We also analyz
作者: GLUT    時(shí)間: 2025-3-22 14:13
Control Charts of Mean by Using Copula Markov SPC and Conditional Distribution by Copula,(Commun Stat: Simul Comput 46:3067–3087, 2017) under serial dependence after accounting for the directional dependence by diverse copula functions. To illustrate the method proposed by Kim et al. (Commun Stat: Simul Comput, 2019), we revisit the case study of Major League Baseball (MLB), where the S
作者: GLUT    時(shí)間: 2025-3-22 20:10
Copula Markov Models for Count Series with Excess Zeros,. In some cases, a specific count, say zero, may occur more often than usual. Additionally, serial dependence might be found among these counts if they are recorded over time. Overlooking the frequent occurrence of zeros and the serial dependence could lead to false inference. In this chapter, Marko
作者: 無辜    時(shí)間: 2025-3-22 23:22

作者: peptic-ulcer    時(shí)間: 2025-3-23 03:55

作者: outskirts    時(shí)間: 2025-3-23 08:20

作者: 作繭自縛    時(shí)間: 2025-3-23 10:45
Estimation Under Normal Mixture Models for Financial Time Series Data,and the Clayton copula for serial dependence, we obtain the corresponding likelihood function. In order to obtain the maximum likelihood estimators, we apply the Newton–Raphson algorithm with appropriate transformations and initial values. In the empirical analysis, the stock price of Dow Jones Industrial Average is analyzed for illustration.
作者: indoctrinate    時(shí)間: 2025-3-23 14:50
Bayesian Estimation Under the ,-Distribution for Financial Time Series,rical Bayes method through the resampling procedure. We provide a Metropolis–Hastings algorithm to simulate the posterior distribution. We also analyze the stock price data in empirical studies for illustration.
作者: 密切關(guān)系    時(shí)間: 2025-3-23 21:28
Writing Assignments: Where Writing Beginsrties of the MLEs. We propose goodness-of-fit methods to test the model assumptions based on a given dataset. In addition, a copula model selection method is discussed. We introduce an R package . to implement the statistical methods of this chapter. Finally, we analyze three real datasets for illustration.
作者: interrupt    時(shí)間: 2025-3-24 01:07

作者: DIKE    時(shí)間: 2025-3-24 05:42

作者: IOTA    時(shí)間: 2025-3-24 06:50
White Passage and Black Pedagogypulas are reviewed, such as the Clayton copula, the Gaussian copula, the Frank copula, and the Joe copula. Finally, we introduce the copula-based Markov chain time series models and their fundamental properties.
作者: 虛弱的神經(jīng)    時(shí)間: 2025-3-24 14:14

作者: 怎樣才咆哮    時(shí)間: 2025-3-24 15:07
Producing Adult Readers: 1930–50rical Bayes method through the resampling procedure. We provide a Metropolis–Hastings algorithm to simulate the posterior distribution. We also analyze the stock price data in empirical studies for illustration.
作者: monologue    時(shí)間: 2025-3-24 22:18
Book 2020It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical
作者: Epidural-Space    時(shí)間: 2025-3-25 00:53
Copula Markov Models for Count Series with Excess Zeros,models, bivariate copula functions such as the bivariate Gaussian, Frank, and Gumbel are chosen to construct a bivariate distribution of two consecutive observations. Moreover, the trivariate Gaussian and max-infinitely divisible copula functions are considered to build the joint distribution of thr
作者: 欺騙手段    時(shí)間: 2025-3-25 05:38
Book 2020imum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods. .
作者: 壓倒性勝利    時(shí)間: 2025-3-25 09:57

作者: antenna    時(shí)間: 2025-3-25 14:16
Writing Assignments: Where Writing Beginsmodels, bivariate copula functions such as the bivariate Gaussian, Frank, and Gumbel are chosen to construct a bivariate distribution of two consecutive observations. Moreover, the trivariate Gaussian and max-infinitely divisible copula functions are considered to build the joint distribution of thr
作者: diabetes    時(shí)間: 2025-3-25 17:05
https://doi.org/10.1007/978-981-15-4998-4Copula; Maximum Likelihood Estimator; Serial Correlation; Markov Chain; Serial Dependence; Statistical Pr
作者: Jocose    時(shí)間: 2025-3-25 22:38
978-981-15-4997-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
作者: condescend    時(shí)間: 2025-3-26 03:04

作者: Instinctive    時(shí)間: 2025-3-26 05:50
SpringerBriefs in Statisticshttp://image.papertrans.cn/c/image/238182.jpg
作者: GEM    時(shí)間: 2025-3-26 11:46
Copula-Based Markov Models for Time Series978-981-15-4998-4Series ISSN 2191-544X Series E-ISSN 2191-5458
作者: 推崇    時(shí)間: 2025-3-26 16:29
White Passage and Black Pedagogy introduce five datasets, namely, the chemical process data, S&P 500 stock market index data, the batting average data in MLB, the stock price data of Dow Jones Industrial Average, and data on the number of arsons.
作者: ineluctable    時(shí)間: 2025-3-26 20:38
Overview of the Book with Data Examples, introduce five datasets, namely, the chemical process data, S&P 500 stock market index data, the batting average data in MLB, the stock price data of Dow Jones Industrial Average, and data on the number of arsons.
作者: 枯燥    時(shí)間: 2025-3-27 00:36
White Passage and Black Pedagogy introduce five datasets, namely, the chemical process data, S&P 500 stock market index data, the batting average data in MLB, the stock price data of Dow Jones Industrial Average, and data on the number of arsons.
作者: 裂縫    時(shí)間: 2025-3-27 05:01
White Passage and Black Pedagogye then introduce Kendall’s tau as a measure of dependence structure for a pair of random variables, and its relationship with a copula. Examples of copulas are reviewed, such as the Clayton copula, the Gaussian copula, the Frank copula, and the Joe copula. Finally, we introduce the copula-based Mark
作者: stress-response    時(shí)間: 2025-3-27 05:54

作者: 伸展    時(shí)間: 2025-3-27 11:04

作者: geometrician    時(shí)間: 2025-3-27 13:56
Producing Adult Readers: 1930–50rkov chain. Due to the computational difficulty of obtaining maximum likelihood estimates, alternatively, we develop Bayesian inference using the empirical Bayes method through the resampling procedure. We provide a Metropolis–Hastings algorithm to simulate the posterior distribution. We also analyz
作者: inferno    時(shí)間: 2025-3-27 17:53

作者: Fantasy    時(shí)間: 2025-3-28 00:30

作者: 弄污    時(shí)間: 2025-3-28 02:07
Mark J. Fiannery0 MHz-CW-Doppler und sahen dessen Bedeutung prim?r in der Beurteilung von ?sophagusvarizen. Er konnte mit der 2,08 mm messenden Sonde die atemabh?ngige Flu?richtung (hepatofugal, hepatopetal) und Blutflu?geschwindigkeit in den Varizen dokumentieren und die insuffizienten Perforansvenen aufspüren. Pe
作者: Fillet,Filet    時(shí)間: 2025-3-28 07:04
Allgemeiner Teil,haufen, denen ein herber Geruch entstr?mt, bilden die groβen Formen der Brauntange, Laminarien und Fucus. wirr durcheinander geworfen; bei n?herer Untersuchung gewahren wir dann breite rote Bl?tter von Delesseria, Büschel von Plocamium und Polysiphonia neben vielen anderen kleineren roten und braune




歡迎光臨 派博傳思國際中心 (http://www.pjsxioz.cn/) Powered by Discuz! X3.5
炎陵县| 安达市| 友谊县| 鄂温| 酒泉市| 乳山市| 铜川市| 耿马| 项城市| 女性| 利辛县| 松阳县| 萨迦县| 柞水县| 广德县| 沁源县| 梧州市| 鄂托克前旗| 包头市| 北流市| 禹州市| 苏尼特右旗| 射洪县| 松滋市| 海城市| 安康市| 多伦县| 呼和浩特市| 贡嘎县| 杭州市| 牡丹江市| 江达县| 长治县| 棋牌| 保康县| 岳阳市| 许昌市| 昌邑市| 沽源县| 诸城市| 克什克腾旗|