Divided we fall, united we stand. Finally writers following logic. As Celente says, you do not need to dive through endless publications to have a honest view of current events. Toggle navigation. There were articles with total references during the period between and , and the average number of references cited per article was Averagely there were 8, references cited per year, and the total number almost increased yearly and shows that the distribution of citations by volumes indicates that the highest number of citations The degree of collaboration is calculated by using the following formula K.
Subramanyam, No Total pages No of contributions Average 12 44 9. Average Pages per Volume Table no 8 point out that journal articles published with a total page of average 8. It is observed that the average length of the articles varied from a minimum of 7. The average number of papers is during the study and the similar type of result has been drawn by Umamaheswari S in the journal of Agronomy and Dr. P Rajendran etc. Table 9 represents the details about country wise distribution of articles in which the maximum articles were contributed by authors from India There were 13 countries whose authors contributed only one article each.
Distribution of contributions — Country — wise There were 5 countries whose authors contributed only one paper each. Distribution of contributions — State- wise The highest number of contributions i.
Generally Indian journals are measured as low profile journals. But the study point out that the Journal of Intellectual Property Rights JIPR has good contributions by Indian authors and also invites foreign authors to publish their contributions. Authorship trends and collaboration pattern in the marine sciences literature: a scientometric study. International Journal of Information Dissemination and Technology, 2 3 , Ginn, L. Annals of Library and Information Studies. Chinese Librarianship: an International Electronic Journal, New Delhi: Crest Publishing House.
Nandi, A. Research contributions in chemistry at the University of Burdwan: An analytical study. Annals of Library and Information Studies, 56 3 , Naseer, M M. Pritchard, A. Statistical bibliography or bibliometrics?
Journal of Documentation, 25 4 , Unfortunately, mean-shift tests may not work well when the series has a trend. If in truth a series has a trend but no mean shift, then a changepoint test designed for zero-trend data often tries to compensate for the mean misspecification by erroneously flagging a changepoint near the record's midpoint.
If the series length is subsegmented about found changepoint times and the subsegments are analyzed, additional changepoints are often erroneously declared. It is therefore desirable to develop homogenization methods that are applicable to data with trends. None of these references identifies an asymptotic statistical distribution for the crucial changepoint existence test.
In fact, the current climate literature seems fractured and is often based on case-by-case simulation, despite the fact which will become apparent here that tractable asymptotic distributions can be derived. Of the above papers, Wang et al. Their penalty for a changepoint occurring at time c , denoted by P c , is derived through trial and error simulations with normal Gaussian distributions.
This results in an ad hoc improvement for the specific models and sample sizes employed, but no general justification is given. The mathematical derivations in this paper explain the necessity for, and provide a specific form for, the penalty term P c , which is appropriate for all sample sizes. Justification under minimal assumptions is given—we require independent model errors, but no distributional assumptions such as normality. This paper seeks to provide a more unified and mathematically justified procedure for changepoint tests for climate time series with possible trends.
The good news is that justifiable test statistics are explicit and can be calculated from regression t tests, which are provided by standard statistical software.
Furthermore, hypothesis testing decision rules can be based on an asymptotic theory that holds in great generality. Correct quantification of the asymptotic distribution of the AMOC test statistic is needed, which is provided in this paper.
For purposes of exposition, attention is restricted to models whose trend slope is constrained to be the same before and after the changepoint time. We provide all technical details so that an interested reader can modify our methods to more complicated models such as those considered in Beaulieu et al.
While several of our asymptotic distributions have appeared in the technical statistics literature, they seem unknown unappreciated in climate settings. For example, the asymptotic properties of the classical standard normal homogeneity test SNHT of Alexandersson are presented here for the first time in a climate venue.
Also, even in the statistical literature, the connection between AMOC changepoint tests and standard regression t tests has not been made clear. The rest of this paper proceeds as follows.
The next section reviews the simple case of a mean shift only no trends and states asymptotic distributions. Section 3 then presents analogous results for regression structures involving a linear trend. Section 4 presents a simulation study that supports the asymptotic theory presented and illuminates some of the properties of the methods. Section 5 shows how the methods can be used to make inferences on two temperature series. Concluding comments are made in section 6.
Comparisons of the different tests are made and some words of caution are presented. Technical derivations are collected into an appendix. Our first result is taken from MacNeill but does not appear to be appreciated in climate settings. The immediate implication is that critical values of C can be calculated.
Specifically, a known expression [see Resnick and Robbins et al. Here, the resulting critical values are provided in Table 1 for various levels of statistical confidence.
Use of these percentiles is generally conservative for a finite n. This will be shown in section 4. In general, likelihood ratio statistics can be difficult to compute, but are very powerful i. Thereby, Table 2 lists simulated critical values of for various values of h and statistical confidence levels. Up to boundary cropping issues, this result provides the asymptotic distribution of the classical standard normal homogeneity test of Alexandersson An alternative to using the percentiles in Table 2 would be to simulate critical values for every sample size n.
Critical values of the likelihood ratio statistic. Values are found by simulating one million samples of a Brownian bridge process. The similarities and differences between the asymptotic distributions in 2. First, 's limit distribution involves the supremum of the square of B z rather than B z.
This is of little concern: taking the largest absolute value or the largest squared value produces the same changepoint time estimator. This factor serves to place greater weight on c values near unity or n. As a result, should have higher power than C when a changepoint occurs near the record's endpoints. Wang et al. Specifically, they propose maximizing P c Z c , where P c is a penalty term derived through trial and error simulation. For practical recommendations, one should prefer if only one test can be considered.
Should the changepoint occur closer to the data boundaries e. In short, it makes sense to compute both statistics but to rely on the likelihood ratio statistic should conclusions conflict. As to what value of h one should use, this is not usually important.
Finally, one does not need Gaussian data for good performance. Unfortunately, when the errors are not zero-mean, the performance of the changepoint tests above can be bad for the reasons discussed in the introduction. This brings us to our next section. For example, Gallagher et al. Unfortunately, when a linear trend is involved, the results of the last section will no longer apply.
This issue, in fact, confused many early statistics authors MacNeill ; Sen ; Kim and Siegmund Nonetheless and similar to what was seen in the last section , examining the CUSUM statistic of will illuminate better methods. Table 3 provides asymptotic percentiles for D. The percentiles are again conservative when applied to scenarios with a finite n. Values are found by simulating one million samples of. Equation 3. This is because any standard statistical software will calculate T c for each admissible changepoint time c.
A t -based test for an unknown changepoint then simply looks at the maximum of T c [or T c 2 ] over all possible c. Such a statistic is also the Gaussian likelihood ratio statistic. As in the simple mean-shift case, one cannot extract a meaningful limit law without first cropping.
Asymptotic percentiles for are given in Table 4. As the next section shows, percentiles are again conservative when applied to scenarios with a finite n see also Robbins et al. Values were found by simulating one million samples of. Notice that requires less computation than as one does not need to compute parameter estimators for each and every c. However, both have the same limiting distribution and hence the same asymptotic detection power. This said, should be slightly more powerful for finite n as it incorporates alternative hypothesis estimators.
Extending the rationale of Wang et al. Elaborating, Wang et al. In effect, Wang is trying to introduce a test statistic with the behavior of. Unfortunately, Wang's statistic cannot be easily calculated or quantified asymptotically, whereas the statistics introduced here are easily calculated and have quantifiable limiting distributions.
For practical recommendations, we suggest using in favor of should conclusions conflict for reasons illustrated in the next section. It remains to derive results 3 and 4, which is done in the appendix. One would have to perform yet another derivation for regression structures employing sinusoidal, quadratic, or exponential terms.
Sinusoidal terms, for example, could arise in the analysis of daily or monthly series. This said, the derivations are similar in spirit and we offer the linear case as perhaps useful guidance. This section uses simulation to assess the efficacy of the methods in section 3. All series are simulated from 3. The performance of all methods seemed invariant of the regression parameters chosen; hence, we report results for the above choices only.
To begin, the no changepoint null hypothesis performance of the methods is studied. For each series length n , one million series were generated from 3. A network of 25 experts trendz range of specialties would rival many university faculties. Read a sample story. By using this site, you agree to the Terms of Use and Privacy Policy. A must-read guide to future trends. The value of a subscription has never been greater. There is no alternative.
A few of the stories in the current issue. Please consider expanding the lead to provide an accessible overview of all important aspects of the article. Gerald Celente gwrald, trend expert, visionary, keynote speaker, is trusted worldwide as the foremost authority on forecasting, analyzing and tracking trends. He had early political experience running a mayoral campaign in Yonkers, New York[ when?
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