Trend, Growth Rate, and Change Point Analysis—A Data Driven Approach

2008 ◽  
Vol 37 (3) ◽  
pp. 498-506 ◽  
Author(s):  
C. T. Jose ◽  
B. Ismail ◽  
S. Jayasekhar
2009 ◽  
Vol 59 (5) ◽  
Author(s):  
Jaromír Antoch ◽  
Marie Hušková

AbstractThe paper deals a class of rank based procedures for detection of changes with adaptively chosen scores. This is a certain continuation of the paper Antoch et al (2008). The limit behavior of the test procedures is studied both under the null as well as under a general class of alternatives. Accompanying simulation study focuses on various alternatives which are often met in practice.


Author(s):  
Aviral Kumar Tiwari ◽  
Cleiton Guollo Taufemback ◽  
Satish Kumar

Psychometrika ◽  
2015 ◽  
Vol 81 (4) ◽  
pp. 1118-1141 ◽  
Author(s):  
Can Shao ◽  
Jun Li ◽  
Ying Cheng

2018 ◽  
Vol 11 (2) ◽  
pp. 420-433 ◽  
Author(s):  
Adem Yavuz Sönmez ◽  
Semih Kale

Abstract The main purpose of this study was to estimate possible climate change effects on the annual streamflow of Filyos River (Turkey). Data for annual streamflow and climatic parameters were obtained from streamflow gauging stations on the river and Bartın, Karabük, Zonguldak meteorological observation stations. Time series analysis was performed on 46 years of annual streamflow data and 57 years of annual mean climatic data from three monitoring stations to understand the trends. Pettitt change-point analysis was applied to determine the change time and trend analysis was performed to forecast trends. To reveal the relationship between climatic parameters and streamflow, correlation tests, namely, Spearman's rho and Kendall's tau were applied. The results of Pettitt change-point analysis pointed to 2000 as the change year for streamflow. Change years for temperature and precipitation were detected as 1997 and 2000, respectively. Trend analysis results indicated decreasing trends in the streamflow and precipitation, and increasing trend in temperature. These changes were found statistically significant for streamflow (p < 0.05) and temperature (p < 0.01). Also, a statistically significant (p < 0.05) correlation was found between streamflow and precipitation. In conclusion, decreasing precipitation and increasing temperature as a result of climate change initiated a decrease in the river streamflow.


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