A comparison between two discordancy tests to identify outlier in Wrapped Normal (WN) samples

This study focuses on comparing the performance of the Robust Circular Distance (RCDU*) (simplified version) and A statistics in detecting a single outlier in the Wrapped Normal (WN) samples. Firstly, this study proposes a simplified version of RCDU statistic. Then, the paper generates the cut-off points for both statistics taken from WN samples via a simulation study. This study also evaluates the performance of both statistics using the proportion of a correct outlier detection. As a result, for a small sample size, the performance of RCDU* and A statistics do not have a huge difference. However, for a large sample size of n=250, A statistic performs slightly better than RCDU* statistic. As an illustration of a practical example, both statistics successfully detected one outlier present in the wind direction data at Kota Bharu station

Confidence interval for parameters estimates in circular simultaneous functional relationship model (CSFRM) for equal variances using normal asymptotic and bootstrap confidence intervals

Few studies have considered the functional relationship model for circular variables. Anuar has proposed a new model of Circular Simultaneous Functional Relationship Model for equal variances. However, the confidence interval for all parameter estimates in this model has not received any consideration in any literature. This paper proposes the confidence interval for all parameter estimates of von Mises distribution in this model. The parameters are estimated using minimum sum (ms) and polyroot function provided in (built-in package) Splus statistical software. The parameters confidence may be obtained from parameter estimation. Those estimation values are obtained by minimizing the negative value of the log-likelihood function. Then, the confidence interval for all parameters based on the bootstrap method will be compared with the normal asymptotic confidence interval via simulation studies. It is found that bootstrap method is the superior method by measuring the performance using coverage probability and expected length. The confidence intervals are illustrated using real wind direction data of Bayan Lepas that collected at 16.3 m above ground level, latitude 05°18’N and longitude 100°16’E. The results showed that the estimate parameters fall between the estimate interval, and we note that the method works well for this model

Notes on the Wild Tomistoma Populations in Western Sarawak, Malaysian Borneo

Tomistoma schlegelii, the Freshwater Malayan Gharial or Tomistoma (local name: buaya jejulong), is secretive in nature; thus, very limited information is currently available on its wild population, especially in Sarawak. The objective of this study is to describe effort in assessing the Tomistoma wild populations in Ulu Sebuyau, Samarahan, and Serian, western Sarawak. Despite many challenges faced, this research has been successful at different levels. There was no Tomistoma seen during day surveys (2014-2015) in tributary of Samarahan River (Samarahan), Bunga-Baki River (Serian), and Kepayang River (Ulu Sebuyau). However, the research team came across two incidents of Tomistoma captured by the local people: (i) an adult male Tomistoma, captured in February 2015 in peat swamp area of Samarahan River tributary, and (ii) a hatchling, caught in Bunga-Baki River in March 2015. The sightings of Tomistoma in Kepayang River were reported by local people in February 2016; however, no individual was captured. The presence of hatchling in Bunga-Baki River indicates that a breeding population is most likely to occur in the area, and this gives hope for future conservation of Tomistoma in Sarawak. All sampling sites recorded almost similar water quality parameters and landscape of peat swamp areas, which previous studies claimed to be the potential Tomistoma habitats. The findings of this study should help relevant state agencies to step up efforts related to conservation of Tomistoma in Sarawak

Modelling wind speed data in Pulau Langkawi with functional relationship

Wind speed influenced weather predictions, aerospace operations, and maritime operations, construction projects. This research aims to examine the relationship between Pulau Langkawi wind speed data during the southwest monsoons in 2019 and 2020. To model wind speed data that follows a normal distribution. An error-in-variables model (EIVM) is utilised, which is a linear functional relationship model (LFRM). The QQ-plots will be utilised to investigate the adequacy of the model’s fit. The maximum likelihood estimation (MLE) approach is employed to estimate the parameters of the model, while the covariance is calculated using the Fisher Information matrix. As a result, it is found that the estimated values demonstrate consistency and reduced dispersion. Thus, the findings could lead to a better knowledge of wind energy prediction

Notes on the Wild Tomistoma Populations in Western Sarawak, Malaysian Borneo

Tomistoma schlegelii, the Freshwater Malayan Gharial or Tomistoma (local name: buaya jejulong), is secretive in nature; thus, very limited information is currently available on its wild population, especially in Sarawak. The objective of this study is to describe effort in assessing the Tomistoma wild populations in Ulu Sebuyau, Samarahan, and Serian, western Sarawak. Despite many challenges faced, this research has been successful at different levels. There was no Tomistoma seen during day surveys (2014-2015) in tributary of Samarahan River (Samarahan), Bunga-Baki River (Serian), and Kepayang River (Ulu Sebuyau). However, the research team came across two incidents of Tomistoma captured by the local people: (i) an adult male Tomistoma, captured in February 2015 in peat swamp area of Samarahan River tributary, and (ii) a hatchling, caught in Bunga-Baki River in March 2015. The sightings of Tomistoma in Kepayang River were reported by local people in February 2016; however, no individual was captured. The presence of hatchling in Bunga-Baki River indicates that a breeding population is most likely to occur in the area, and this gives hope for future conservation of Tomistoma in Sarawak. All sampling sites recorded almost similar water quality parameters and landscape of peat swamp areas, which previous studies claimed to be the potential Tomistoma habitats. The findings of this study should help relevant state agencies to step up efforts related to conservation of Tomistoma in Sarawak

On discordance test for the wrapped normal data

This paper focuses on detecting outliers in the circular data which follow the wrapped normal distribution. We considered four discordance tests based on M, C, D and A statistics. The cut-off points of the four tests were obtained and the performance of the detection procedures was studied via simulations. In general, we showed that the discordance test based on the A statistic outperforms the other tests in all cases. For illustration, the city of Kuantan wind direction data set was considered

Outlier detection in a circular regression model

Recently, there is strong interest on the subject of outlier problem in circular data. In this paper, we focus on detecting outliers in a circular regression model proposed by Down and Mardia. The basic properties of the model are available including the exact form of covariance matrix of the parameters. Hence, we intend to identify outliers in the model by looking at the effect of the outliers on the covariance matrix. The method resembles closely the COVRATIO statistic for the case of linear regression problem. The corresponding critical values and the performance of the outlier detection procedure are studied via simulations. For illustration, we apply the procedure on the wind data set

A Half-Circular Distribution on a Circle

Up to now, circular distributions are defined in [0,2 π), except for axial distributions on a semicircle. However, some circular data lie within just half of this range and thus may be better fitted by a half-circular distribution, which we propose and develop in this paper using the inverse stereographic projection technique on a gamma distributed variable. The basic properties of the distribution are derived while its parameters are estimated using the maximum likelihood estimation method. We show the practical value of the distribution by applying it to an eye data set obtained from a glaucoma clinic at the University of Malaya Medical Centre, Malaysia. © 2019 Penerbit Universiti Kebangsaan Malaysia. All rights reserved