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| 2. |
- Ahmed, Nur, et al.
(författare)
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Impact of climate change on rice insect pests and their natural enemies
- 2013
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Konferensbidrag (refereegranskat)abstract
- Rice is one of the important staple foods for half of the world population particularly Asian countries for their livelihood, socio-economic and nutrition. Global warming is predicted to increase frequency of precipitation/rainfall, intensity of drought and solar-radiation/UV-B radiation which might affect the intensity and severity of rice pests in one hand, but also change in other friendly arthropods on the other hand. The present studies discuss the influence of climatic factors (temperature and rainfall) on yellow stem borer (YSB), brown planthopper (BPH), green leafhopper (GLH) and their natural enemies (spider, lady bird beetle, green mirid bug). Light trap and sweep net catches of arthropods from different rice habitats were used in this study. For GLH there is a strong periodicity at 6 months and a somewhat weaker periodicity at 12 months followed by an even weaker periodicity at 3 months, especially valid for both methods of data collection (light trap and sweep-net data). Finally, for GMB there is a strong periodicity at 6 months and a somewhat weaker periodicity at 3 months followed by an even weaker periodicity at 4 months. There is a general increasing trend over the ten years seems to be present in the GLH. This corresponds to that the abundance in 2005 is generally 15 times larger than in January 1996. For LBB, there is an increasing trend of log abundance of LBB over time and shows a strong periodicity at 3 months and a somewhat weaker periodicity at 4 months followed by an even weaker periodicity at about 6 months. For Spider there is a strong periodicity at 2.4 months and a somewhat weaker periodicity at 4 months followed by an even weaker periodicities at about 3 months and 6 months. Results show an increase of maximum temperature of approximately 0.5 to 1°C over 10 years.
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| 3. |
- Almasri, Abdullah, et al.
(författare)
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Impact of the periodicity and trend on the FD parameter estimation
- 2007
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Ingår i: Journal of Statistical Computation and Simulation. - : Informa UK Limited. - 1563-5163 .- 0094-9655. ; 77:1, s. 79-87
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Tidskriftsartikel (refereegranskat)abstract
- It is well known that one of the features of long-memory processes is that they tend to have what looks like trends and cycles. A consequence of this property is that it is difficult to distinguish a long-memory process from a nonstationary process. In this paper, we study the impact of the periodicity and trend on different methods for estimating the long-memory processes parameter d.
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| 4. |
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| 5. |
- Bergman, Jakob, et al.
(författare)
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A measure of dependence between two compositions
- 2012
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Ingår i: Australian & New Zealand Journal of Statistics. - 1467-842X. ; 54:4, s. 451-461
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Tidskriftsartikel (refereegranskat)abstract
- We consider the problem of describing the correlation between two compositions. Using a bicompositional Dirichlet distribution, we calculate a joint correlation coefficient, based on the concept of information gain, between two compositions. Numerical values of the joint correlation coefficient are calculated for compositions of two and three components. We also present an estimator of the joint correlation coefficient for a sample from a bicompositional Dirichlet distribution. Two confidence intervals are also presented and we examine their empirical confidence coefficient using Monte Carlo study. Finally we apply the estimator to a data set analysing the correlation between the 1967 and 1997, and the 1977 and 1997 compositions of the government gross domestic product for the 50 U.S. states and District of Columbia.
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| 6. |
- Bergman, Jakob, et al.
(författare)
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A measure of dependence between two compositions
- 2009
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- A composition is a vector of positive components summing to a constant. We consider the problem of describing the correlation between two compo- sitions. Using a bicompositional Dirichlet distribution, we calculate a joint correlation coefficient, based on the concept of information gain, between two compositions. Numerical values of the joint correlation coefficient are calcu- lated for compositions of two and three components.
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| 7. |
- Bergman, Jakob, et al.
(författare)
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Are the Sweden Democrats really Sweden’s largest party? A maximum likelihood ratio test on the simplex
- 2015
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In August 2015 a Swedish newspaper claimed that the Sweden Democrats were the largest political party in Sweden based on the results of single poll. We ask ourselves if this is a correct conclusion, considering the fact that the three largest parties in the poll were of roughly the same size. We analyse the parameter space and identify the subspace where the Sweden Democrats are the largest party. Using this we construct a maximum likelihood ratio test and derive its distribution under the null hypothesis. We finally apply our test to the data and obtaining a p-value between 0.09 and 0.14 are able to refute the claim in the newspaper. Based on the available data one cannot draw the conclusion that the Sweden Democrats are the largest party in Sweden.
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| 8. |
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| 9. |
- Bergman, Jakob, et al.
(författare)
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Compositional Loess modeling
- 2011
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Ingår i: Proceedings of the 4th International Workshop on Compositional Data Analysis. - 9788487867767
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Cleveland (1979) is usually credited with the introduction of the locally weighted regression, Loess. The concept was further developed by Cleveland and Devlin (1988). The general idea is that for an arbitrary number of explanatory data points xi the value of a dependent variable is estimated ŷi. The ŷi is the fitted value from a dth degree polynomial in xi. (In practice often d = 1.) The ŷi is fitted using weighted least squares, WLS, where the points xk (k = 1, ..., n) closest to xi are given the largest weights. We define a weighted least squares estimation for compositional data, C-WLS. In WLS the sum of the weighted squared Euclidean distances between the observed and the estimated values is minimized. In C-WLS we minimize the weighted sum of the squared simplicial distances (Aitchison, 1986, p. 193) between the observed compositions and their estimates. We then define a compositional locally weighted regression, C-Loess. Here a composition is assumed to be explained by a real valued (multivariate) variable. For an arbitrary number of data points xi we for each xi fit a dth degree polynomial in xi yielding an estimate ŷi of the composition yi. We use C-WLS to fit the polynomial giving the largest weights to the points xk (k = 1, ..., n) closest to xi. Finally the C-Loess is applied to Swedish opinion poll data to create a poll-of-polls time series. The results are compared to previous results not acknowledging the compositional structure of the data.
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| 10. |
- Bergman, Jakob, et al.
(författare)
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Poll of polls: A compositional loess model
- 2014
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Ingår i: Scandinavian Journal of Statistics. - : Wiley. - 1467-9469 .- 0303-6898. ; 41:2, s. 301-310
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Tidskriftsartikel (refereegranskat)abstract
- A large number of polls on party preferences are published today. In order to get an estimate of the changes in political opinion, the polls may be combined into a poll of polls. We discuss a method for combining polls using the fact that they are compositions and respecting the properties of the compositional sample space (the simplex). The method is easily implemented and the estimate may be computed in linear time. We provide an example with Swedish data from year 2007 to 2010. The method also allows us to present the deviations between the estimated compositions and the observed. In the data set, we note e.g. differences between different polling institutes.
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