More on estimating the statistical significance of cross-dating positions for "floating" tree-ring series

1994 ◽  
Vol 24 (2) ◽  
pp. 427-429 ◽  
Author(s):  
David K. Yamaguchi
Keyword(s):  
Correlation Analysis ◽  
Tree Ring ◽  
Cross Correlation ◽  
Statistical Significance ◽  
Correlation Coefficients ◽  
Significance Levels ◽  
Cross Correlations ◽  
Student’S T ◽  
T Values ◽  
Cross Dating

Tabulated Student's t-values and climatic insensitivity among inner tree-ring widths can bias estimates of statistical significance for cross correlations relating "floating" and master tree-ring series. These biases can be removed by (i) directly computing significance levels for cross-correlation coefficients at dating positions and (ii) deleting insensitive inner rings from a dated floating sample before final correlation analysis. The number of early rings to delete can be determined from plots of cross-correlation coefficients linking a dated floating series of artificially decreasing length with a master series. These modifications improve the precision of Yamaguchi and Allen's approach (D.K. Yamaguchi and G.L. Allen. 1992. Can. J. For. Res. 22: 1215–1221) for estimating significance.

A new computer program for estimating the statistical significance of cross-dating positions for "floating" tree-ring series

1992 ◽  
Vol 22 (9) ◽  
pp. 1215-1221 ◽  
Author(s):  
David K. Yamaguchi ◽  
George L. Allen
Keyword(s):  
Tree Ring ◽  
Moving Average ◽  
Statistical Significance ◽  
Control Program ◽  
Fortran Program ◽  
Data Quality Control ◽  
Quality Control Program ◽  
Significance Level ◽  
False Rings ◽  
Cross Dating

CORREL is a FORTRAN program that employs cross correlation to (i) determine potential cross-dating (matching) positions for "floating" (undated) ring series; (ii) detect missing or false rings; and (iii) estimate the statistical significance of potential dating positions. To work properly, CORREL input data must be detrended and modeled using the autoregressive moving average procedure. To guard against spurious dating, the output's best date should be checked for dating consistency. The significance level of the best date is obtained by adjusting its single-dating-trial significance for multiplicity (repeated dating trials). Ideally, COREL should be used with the detrending tree-ring programs ARSTAN or INDEX, and with the data quality-control program COFECHA.

Multiscale Multifractal Detrended Cross-Correlation Analysis of High-Frequency Financial Time Series

2019 ◽  
Vol 18 (03) ◽  
pp. 1950014 ◽  
Author(s):  
Jingjing Huang ◽  
Danlei Gu
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
High Frequency ◽  
Cross Correlation ◽  
Financial Time Series ◽  
Chinese Market ◽  
Change Of Scale ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). This method is based on the Hurst surface and can be used to study the non-linear relationship between two time series. By sweeping through all the scale ranges of the multifractal structure of the complex system, it can present more information than the multifractal detrended cross-correlation analysis (MF-DCCA). In this paper, we use the MM-DCCA method to study the cross-correlations between two sets of artificial data and two sets of 5[Formula: see text]min high-frequency stock data from home and abroad. They are SZSE and SSEC in the Chinese market, and DJI and NASDAQ in the US market. We use Hurst surface and Hurst exponential distribution histogram to analyze the research objects and find that SSEC, SZSE and DJI, NASDAQ all show multifractal properties and long-range cross-correlations. We find that the fluctuation of the Hurst surface is related to the positive and negative of [Formula: see text], the change of scale range, the difference of national system, and the length of time series. The results show that the MM-DCCA method can give more abundant information and more detailed dynamic processes.

ON THE APPLICATION OF THE CROSS-CORRELATIONS IN THE CHINESE FUND MARKET: DESCRIPTIVE PROPERTIES AND SCALING BEHAVIORS

2011 ◽  
Vol 14 (01) ◽  
pp. 97-109
Author(s):  
WEIBING DENG ◽  
WEI LI ◽  
XU CAI ◽  
QIUPING A. WANG
Keyword(s):  
Correlation Matrix ◽  
Cross Correlation ◽  
Matrix Theory ◽  
Factorial Moment ◽  
Correlation Coefficients ◽  
Mean Value ◽  
Distribution Of Eigenvalues ◽  
Cross Correlations ◽  
The Cross ◽  
Simple Definition

On the basis of the relative daily logarithmic returns of 88 different funds in the Chinese fund market (CFM) from June 2005 to October 2009, we construct the cross-correlation matrix of the CFM. It is shown that the logarithmic returns follow an exponential distribution, which is commonly shared by some emerging markets. We hereby analyze the statistical properties of the cross-correlation coefficients in different time periods, such as the distribution, the mean value, the standard deviation, the skewness and the kurtosis. By using the method of the scaled factorial moment, we observe the intermittence phenomenon in the distribution of the cross-correlation coefficients. Also by employing the random matrix theory (RMT), we find a few isolated large eigenvalues of the cross-correlation matrix, and the distribution of eigenvalues exhibits the power-law tails. Furthermore, we study the features of the correlation strength with a simple definition.

MULTISCALE DETRENDED CROSS-CORRELATION ANALYSIS OF STOCK MARKETS

Fractals ◽  
2014 ◽  
Vol 22 (04) ◽  
pp. 1450007 ◽  
Author(s):  
YI YIN ◽  
PENGJIAN SHANG
Keyword(s):  
Correlation Analysis ◽  
Stock Markets ◽  
Cross Correlation ◽  
Statistical Characteristics ◽  
Detailed Knowledge ◽  
Stock Indices ◽  
Regional Markets ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997–2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and issue.

scholarly journals Relationships of total COVID-19 cases and deaths with ten demographic, economic and social indicators

2020 ◽  
Author(s):  
Dimitar Valev
Keyword(s):  
Population Density ◽  
Statistical Significance ◽  
Social Indicators ◽  
Composite Index ◽  
Correlation Coefficients ◽  
Statistical Relationships ◽  
Student’S T ◽  
Relationship Of ◽  
The Relationship ◽  
Economic And Social Indicators

AbstractThe statistical relationships of total COVID-19 Cases and Deaths per million populations in 45 countries, where 85.8% of the world’s population lives with 10 demographic, economic and social indicators were studied. Data for 28 May 2020 were used in the main calculations. The relationship of Deaths per million population and total Cases per million population is very close and reaches correlation coefficient R = 0.926. It is interesting that the close correlations were found of Cases and Deaths per 1 million with a purely economic index like GDP PPP per capita, where R = 0.687 and R = 0.660, respectively. Even more close correlations were found of Cases and Deaths per 1 million with a composite index HDI, where the correlation coefficients reach 0.724 and 0.680, respectively. The main reason for these paradoxical results is the underestimation of pandemic restrictions in the form of masks, social distance and disinfection in most of these countries. Other indicators (excluding Gini index and Population Density) also show statistically significant correlations with Cases and Deaths per 1 million with correlation coefficients from 0.432 to 0.634. The statistical significance of the found correlations determined using Student’s t-test was p <0.0001. Surprisingly, there was no statistically significant correlation between Cases and Deaths with Population Density. To check whether there is a change in the correlations with the development of the pandemic, a statistical analysis was made for four different dates – 9 April, 28 May, 7 August and 30 November 2020. It was found that the correlation coefficients of COVID-19 cases and Deaths with the rest indicators decrease during the pandemic.

scholarly journals Bireysel Barışa Yönelik Tutum Ölçeğinin Geliştirilmesi: Geçerlik ve Güvenirlik Çalışmaları / Development of a Scale Measuring Attitudes towards Individual Peace: A Validity and Reliability Study

2018 ◽  
Vol 7 (1) ◽  
pp. 398
Author(s):  
Bahadır Kılcan
Keyword(s):  
Factor Analysis ◽  
Secondary School ◽  
Secondary School Students ◽  
Statistical Significance ◽  
Correlation Coefficients ◽  
Validity And Reliability ◽  
School Students ◽  
Chi Square ◽  
Significance Levels ◽  
Students Attitudes

<p><strong>Abstract</strong></p><p>This study aims to develop a scale to measure eight-grade secondary school students' attitudes towards individual peace. The items of the scale have been prepared by the researcher based on a literature review. The study sample included 223 eight grade students from different schools in the Mamak district of Ankara for the 2015-2016 school year. At the end of the analysis, the correlation coefficients obtained from item-factor total and adjusted correlation were found to be above .21 and all items were statistically significant. In the exploratory factor analysis (EFA), the scale items were split into four dimensions: "State before Peace", "Factors for Peace", "Factors for Sulking" and "Assitance in Peacemaking". The Chi-square (X2) value appropriate for the model developed based on the results of the Confirmatory Factor Analysis (CFA) and statistical significance levels showed that the proposed model was appropriate for the collected data. Reliability coefficients tested for the whole scale and its sub-dimensions revealed that the scale was suitable to measure eight-grade secondary school students' attitudes towards peace.</p><p> </p><p><strong>Öz</strong></p><p>Bu çalışmanın amacı, ortaokul sekizinci sınıf öğrencilerinin bireysel barışa yönelik tutumlarının belirlenmesinde kullanılacak bir ölçme aracı geliştirmektir. Ölçme aracının maddeleri araştırmacı tarafından ilgili alanyazın incelenerek hazırlanmıştır. Araştırmanın çalışma grubunu 2015-2016 öğretim yılının bahar döneminde Ankara İli Mamak İlçesinde bulunan okullarda öğrenim gören toplam 223 sekizinci sınıf öğrencisi oluşturmaktadır. Yapılan istatistikler sonucunda ölçeğin madde-faktör toplam ve düzeltilmiş korelasyonlarında elde edilen korelasyon katsayıları .21’in üzerinde olduğu ve tüm maddelerin istatiksel olarak anlamlı olduğu saptanmıştır. Yapılan açımlayıcı faktör analizi (AFA) sonucunda ölçek maddeleri; “Barışma Öncesi Durum”, “Barışma İçin Etmenler”, “Küsme İçin Etmenler” ve “Barışmada Yardım” olmak üzere dört boyutta toplanmıştır. Çalışma kapsamında yapılan doğrulayıcı faktör analizi (DFA) sonuçlarına göre ölçek için oluşturulan modele uygun Ki-kare (X<sup>2</sup>) değeri ve istatistikî anlamlılık düzeyleri, önerilen modelin toplanan verilere uygun olduğunu göstermiştir. Ölçeğin geneline ve alt boyutlarına yönelik test edilen güvenirlik katsayıları, ortaokul sekizinci sınıf öğrencilerinin bireysel barışa yönelik tutumlarını ölçmede kullanılabilecek nitelikte olduğunu ortaya koymuştur.</p>

scholarly journals Impacts of Aerosol Loading in the Hindu Kush Himalayan Region Based on MERRA-2 Reanalysis Data

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1290
Author(s):  
Shantikumar S. Ningombam ◽  
Umesh Chandra Dumka ◽  
Sivasamy Kalamani Mugil ◽  
Jagdish Chandra Kuniyal ◽  
Rakesh K. Hooda ◽  
...  
Keyword(s):  
Anthropogenic Activities ◽  
Statistical Significance ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Reanalysis Data ◽  
Climatic Conditions ◽  
Energy Demands ◽  
Hindu Kush ◽  
Student’S T ◽  
The Impact

The impacts of climate change have severely affected geosphere, biosphere and cryosphere ecosystems in the Hindu Kush Himalayan (HKH) region. The impact has been accelerating further during the last few decades due to rapid increase in anthropogenic activities such as modernization, industrialization and urbanization, along with energy demands. In view of this, the present work attempts to examine aerosol optical depth (AOD) over the HKH region using the long-term homogeneous MERRA-2 reanalysis data from January, 1980 to December, 2020. The AOD trends are examined statistically with student’s t-test (t). Due to a vast landmass, fragile topography and harsh climatic conditions, we categorized the HKH region into three sub-regions, namely, the northwestern and Karakoram (HKH1), the Central (HKH2) and the southeastern Himalaya and Tibetan Plateau (HKH3). Among the sub-regions, the significant enhancement of AOD is observed at several potential sites in the HKH2 region, namely, Pokhara, Nainital, Shimla and Dehradun by 55.75 × 10−4 ± 3.76 × 10−4, 53.15 × 10−4 ± 3.94 × 10−4, 51.53 × 10−4 ± 4.99 × 10−4 and 39.16 × 10−4 ± 4.08 × 10−4 AOD year−1 (550 nm), respectively, with correlation coefficients (Rs) of 0.86 to 0.93. However, at a sub-regional scale, HKH1, HKH2 and HKH3 exhibit 23.33 × 10−4 ± 2.28 × 10−4, 32.20 × 10−4 ± 2.58 × 10−4 and 9.48 × 10−4 ± 1.21 × 10−4 AOD year−1, respectively. The estimated trends are statistically significant (t > 7.0) with R from 0.81 to 0.91. Seasonally, the present study also shows strong positive AOD trends at several potential sites located in the HKH2 region, such as Pokhara, Nainital, Shimla and Dehradun, with minimum 19.81 × 10−4 ± 3.38 × 10−4 to maximum 72.95 × 10−4 ± 4.89 × 10−4 AOD year−1 with statistical significance. In addition, there are also increasing AOD trends at all the high-altitude background sites in all seasons.

A Multifractal Cross-Correlation Analysis of Economic Policy Uncertainty: Evidence from China and US

2021 ◽  
pp. 2150041
Author(s):  
Ruwei Zhao ◽  
Peng-Fei Dai
Keyword(s):  
Economic Policy ◽  
Correlation Analysis ◽  
Cross Correlation ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Economic Fluctuation ◽  
Cross Correlation Analysis ◽  
Uncertainty Index ◽  
Cross Correlations ◽  
Renyi Exponent

In this study, we utilized the prevailing economic policy uncertainty index (EPU) as the proxy of state economic fluctuation and investigated Sino–US economic fluctuation long horizon cross-correlation with a multifractal detrended cross-correlation analysis (MF-DCCA). With the MF-DCCA approach, we found a reliable long-range cross-correlation between China and US EPU changes. In addition, we discovered that a power law cross-correlation existed for the variation of most scaling orders. However, no persistence of cross-correlations was detected within the Sino–US EPU change series. Additionally, we implemented Rényi exponent and spectrum singularity checks. Both the examination results proved series multifractality with the presented arch-shaped curves. We further calculated the Hölder exponent bounds within each series and found that the China EPU changes had maximal multifractality with the largest exponent difference.

Effect of Weather on Agricultural Futures Markets on the Basis of DCCA Cross-Correlation Coefficient Analysis

2016 ◽  
Vol 15 (02) ◽  
pp. 1650012 ◽  
Author(s):  
Guangxi Cao ◽  
Cuiting He ◽  
Wei Xu
Keyword(s):  
Correlation Analysis ◽  
Futures Markets ◽  
Cross Correlation ◽  
Moving Average ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Fluctuation Analysis ◽  
Cross Correlation Analysis ◽  
Agricultural Futures

This study investigates the correlation between weather and agricultural futures markets on the basis of detrended cross-correlation analysis (DCCA) cross-correlation coefficients and [Formula: see text]-dependent cross-correlation coefficients. In addition, detrended fluctuation analysis (DFA) is used to measure extreme weather and thus analyze further the effect of this condition on agricultural futures markets. Cross-correlation exists between weather and agricultural futures markets on certain time scales. There are some correlations between temperature and soybean return associated with medium amplitudes. Under extreme weather conditions, weather exerts different influences on different agricultural products; for instance, soybean return is greatly influenced by temperature, and weather variables exhibit no effect on corn return. Based on the detrending moving-average cross-correlation analysis (DMCA) coefficient and DFA regression results are similar to that of DCCA coefficient.

scholarly journals X-ray cross-correlation analysis of the low-mass X-ray binary 4U 1636-53

2014 ◽  
Vol 10 (S306) ◽  
pp. 397-399
Author(s):  
Ya-Juan Lei
Keyword(s):  
Correlation Function ◽  
Correlation Analysis ◽  
Cross Correlation ◽  
X Rays ◽  
X Ray ◽  
Cross Correlation Analysis ◽  
Low Mass ◽  
Cross Correlations ◽  
The Cross ◽  
Positive Correlations

AbstractWe analyze the cross-correlation function of the soft and hard X-rays of the atoll source 4U 1636-53 with RXTE data. The results show that the cross-correlations evolve along the different branches of the color-color diagram. At the lower left banana states, we have both positive and ambiguous correlations, and positive correlations are dominant for the lower banana and the upper banana states. The anti-correlation is detected at the top of the upper banana states. The cross-correlations of two atoll sources 4U 1735-44 and 4U 1608-52 have been studied in previous work, and the anti-correlations are detected at the lower left banana or the top of the upper banana states. Our results show that, in the 4U 1636-53, the distribution of the cross-correlations in the color-color diagram is similar to those of 4U 1735-44 and 4U 1608-52, and confirm further that the distribution of cross-correlations in color-color diagram could be correlated with the luminosity of the source.

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