This study aimed to examine the performance of the Siegel-Tukey and Savage tests on data sets with heterogeneous variances. The analysis, considering Normal, Platykurtic, and Skewed distributions and a standard deviat...This study aimed to examine the performance of the Siegel-Tukey and Savage tests on data sets with heterogeneous variances. The analysis, considering Normal, Platykurtic, and Skewed distributions and a standard deviation ratio of 1, was conducted for both small and large sample sizes. For small sample sizes, two main categories were established: equal and different sample sizes. Analyses were performed using Monte Carlo simulations with 20,000 repetitions for each scenario, and the simulations were evaluated using SAS software. For small sample sizes, the I. type error rate of the Siegel-Tukey test generally ranged from 0.045 to 0.055, while the I. type error rate of the Savage test was observed to range from 0.016 to 0.041. Similar trends were observed for Platykurtic and Skewed distributions. In scenarios with different sample sizes, the Savage test generally exhibited lower I. type error rates. For large sample sizes, two main categories were established: equal and different sample sizes. For large sample sizes, the I. type error rate of the Siegel-Tukey test ranged from 0.047 to 0.052, while the I. type error rate of the Savage test ranged from 0.043 to 0.051. In cases of equal sample sizes, both tests generally had lower error rates, with the Savage test providing more consistent results for large sample sizes. In conclusion, it was determined that the Savage test provides lower I. type error rates for small sample sizes and that both tests have similar error rates for large sample sizes. These findings suggest that the Savage test could be a more reliable option when analyzing variance differences.展开更多
The study investigates long-term changes in annual and seasonal rainfall patterns in the Indira Sagar Region of Madhya Pradesh, India, from 1901 to 2010. Agriculture sustainability, food supply, natural resource devel...The study investigates long-term changes in annual and seasonal rainfall patterns in the Indira Sagar Region of Madhya Pradesh, India, from 1901 to 2010. Agriculture sustainability, food supply, natural resource development, and hydropower system reliability in the region rely heavily on monsoon rainfall. Monthly rainfall data from three stations (East Nimar, Barwani, and West Nimar) were analyzed. Initially, the pre-whitening method was applied to eliminate serial correlation effects from the rainfall data series. Subsequently, statistical trends in annual and seasonal rainfall were assessed using both parametric (student-t test) and non-parametric tests [Mann-Kendall, Sen’s slope estimator, and Cumulative Sum (CUSUM)]. The magnitude of the rainfall trend was determined using Theil-Sen’s slope estimator. Spatial analysis of the Mann-Kendall test on an annual basis revealed a statistically insignificant decreasing trend for Barwani and East Nimar and an increasing trend for West Nimar. On a seasonal basis, the monsoon season contributes a significant percentage (88.33%) to the total annual rainfall. The CUSUM test results indicated a shift change detection in annual rainfall data for Barwani in 1997, while shifts were observed in West and East Nimar stations in 1929. These findings offer valuable insights into regional rainfall behavior, aiding in the planning and management of water resources and ecological systems.展开更多
Background: Bivariate count data are commonly encountered in medicine, biology, engineering, epidemiology and many other applications. The Poisson distribution has been the model of choice to analyze such data. In mos...Background: Bivariate count data are commonly encountered in medicine, biology, engineering, epidemiology and many other applications. The Poisson distribution has been the model of choice to analyze such data. In most cases mutual independence among the variables is assumed, however this fails to take into accounts the correlation between the outcomes of interests. A special bivariate form of the multivariate Lagrange family of distribution, names Generalized Bivariate Poisson Distribution, is considered in this paper. Objectives: We estimate the model parameters using the method of maximum likelihood and show that the model fits the count variables representing components of metabolic syndrome in spousal pairs. We use the likelihood local score to test the significance of the correlation between the counts. We also construct confidence interval on the ratio of the two correlated Poisson means. Methods: Based on a random sample of pairs of count data, we show that the score test of independence is locally most powerful. We also provide a formula for sample size estimation for given level of significance and given power. The confidence intervals on the ratio of correlated Poisson means are constructed using the delta method, the Fieller’s theorem, and the nonparametric bootstrap. We illustrate the methodologies on metabolic syndrome data collected from 4000 spousal pairs. Results: The bivariate Poisson model fitted the metabolic syndrome data quite satisfactorily. Moreover, the three methods of confidence interval estimation were almost identical, meaning that they have the same interval width.展开更多
[Objectives]To reduce suicidal ideation and suicidal behavior through initial screening of patients with suicidal tendencies and implementing suicide prevention interventions during their hospitalization.[Methods]The ...[Objectives]To reduce suicidal ideation and suicidal behavior through initial screening of patients with suicidal tendencies and implementing suicide prevention interventions during their hospitalization.[Methods]The Taihe Emotion-distress Index(THEI)was used to conduct pre-admission and post-discharge tests to explore the effects of suicide prevention measures during hospitalization on the alleviation of the disease and the reduction of suicidal behaviors.The study selected patients who were diagnosed with depression in the psychological outpatient department of Taihe Hospital from April 2019 to September 2019 and had to be hospitalized,including patients with moderate depressive episodes,severe depressive episodes with or without psychotic symptoms,and patients with suicidal thoughts and self-harming behaviors.[Results]The pre-admission and post-discharge test data of hospitalized patients were analyzed,and the non-parametric paired sample T test was carried out,and the result was P<0.05,showing that there are significant differences between the pre-admission and post-discharge test data.[Conclusions]The measures of suicide prevention intervention are effective to a certain extent.展开更多
State is in the South East geopolitical zone of Nigeria. The major occupation of the people in this region is trading and farming, which depends on rainfall and other climatic factors. This paper presents statistical ...State is in the South East geopolitical zone of Nigeria. The major occupation of the people in this region is trading and farming, which depends on rainfall and other climatic factors. This paper presents statistical and trend analyses of the rainfall in some selected stations in Anambra State, which includes Ifite-Ogwari, Awka, Onitsha and Ihiala. Rainfall data for a period of 1971-2010 were obtained from Climate Research Unit (CRU). The existence of trend and statistical analyses was conducted on monthly total rainfalls using non-parametric techniques. The study revealed that overall averages of yearly and monthly total rainfall were 5798.78 mm and 1739.62 mm in Ifite-Ogwari, 6051.8 mm and 1815 mm in Awka, 6288.87 mm and 1886.88 mm in Onitsha, and 6637.19 mm and 1997.1 mm in Ihiala. Yearly total rainfall has Mann-Whitney of 26 and 41 between 1971 and 1990, 1991 and 2010 respectively in Ifite-Ogwari, 32 and 42 between 1971 and 1990, 1991 and 2010 respectively in Awka, 42 and 39 between 1971 and 1990, 1991 and 2010 respectively in Onitsha, and 33 and 45 between 1971 and 1990, 1991 and 2010 respectively in Ihiala. These parameters show that there are significant trends in the rainfall in term of yearly total for the period. Sen’s estimator revealed that there were significant downward trends for yearly total (-0.775 mm/year) and (-0.094 mm/year) within the period of 1971-1990 and 1991-2010 in Ifite-Ogwari. There was an upward trend of yearly total (1.841 mm/year) between 1971 and1990, whereas there was a downward trend of yearly total (-0.211) between 1991 and 2010 in Awka. It was concluded that there was a significant downward trend in the yearly total and mean rainfalls in Ifite-Ogwari, Awka, Onitsha and Ihiala in the last four decades (40 years), which could be attributed to climate change.展开更多
The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta re...The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.展开更多
文摘This study aimed to examine the performance of the Siegel-Tukey and Savage tests on data sets with heterogeneous variances. The analysis, considering Normal, Platykurtic, and Skewed distributions and a standard deviation ratio of 1, was conducted for both small and large sample sizes. For small sample sizes, two main categories were established: equal and different sample sizes. Analyses were performed using Monte Carlo simulations with 20,000 repetitions for each scenario, and the simulations were evaluated using SAS software. For small sample sizes, the I. type error rate of the Siegel-Tukey test generally ranged from 0.045 to 0.055, while the I. type error rate of the Savage test was observed to range from 0.016 to 0.041. Similar trends were observed for Platykurtic and Skewed distributions. In scenarios with different sample sizes, the Savage test generally exhibited lower I. type error rates. For large sample sizes, two main categories were established: equal and different sample sizes. For large sample sizes, the I. type error rate of the Siegel-Tukey test ranged from 0.047 to 0.052, while the I. type error rate of the Savage test ranged from 0.043 to 0.051. In cases of equal sample sizes, both tests generally had lower error rates, with the Savage test providing more consistent results for large sample sizes. In conclusion, it was determined that the Savage test provides lower I. type error rates for small sample sizes and that both tests have similar error rates for large sample sizes. These findings suggest that the Savage test could be a more reliable option when analyzing variance differences.
文摘The study investigates long-term changes in annual and seasonal rainfall patterns in the Indira Sagar Region of Madhya Pradesh, India, from 1901 to 2010. Agriculture sustainability, food supply, natural resource development, and hydropower system reliability in the region rely heavily on monsoon rainfall. Monthly rainfall data from three stations (East Nimar, Barwani, and West Nimar) were analyzed. Initially, the pre-whitening method was applied to eliminate serial correlation effects from the rainfall data series. Subsequently, statistical trends in annual and seasonal rainfall were assessed using both parametric (student-t test) and non-parametric tests [Mann-Kendall, Sen’s slope estimator, and Cumulative Sum (CUSUM)]. The magnitude of the rainfall trend was determined using Theil-Sen’s slope estimator. Spatial analysis of the Mann-Kendall test on an annual basis revealed a statistically insignificant decreasing trend for Barwani and East Nimar and an increasing trend for West Nimar. On a seasonal basis, the monsoon season contributes a significant percentage (88.33%) to the total annual rainfall. The CUSUM test results indicated a shift change detection in annual rainfall data for Barwani in 1997, while shifts were observed in West and East Nimar stations in 1929. These findings offer valuable insights into regional rainfall behavior, aiding in the planning and management of water resources and ecological systems.
文摘Background: Bivariate count data are commonly encountered in medicine, biology, engineering, epidemiology and many other applications. The Poisson distribution has been the model of choice to analyze such data. In most cases mutual independence among the variables is assumed, however this fails to take into accounts the correlation between the outcomes of interests. A special bivariate form of the multivariate Lagrange family of distribution, names Generalized Bivariate Poisson Distribution, is considered in this paper. Objectives: We estimate the model parameters using the method of maximum likelihood and show that the model fits the count variables representing components of metabolic syndrome in spousal pairs. We use the likelihood local score to test the significance of the correlation between the counts. We also construct confidence interval on the ratio of the two correlated Poisson means. Methods: Based on a random sample of pairs of count data, we show that the score test of independence is locally most powerful. We also provide a formula for sample size estimation for given level of significance and given power. The confidence intervals on the ratio of correlated Poisson means are constructed using the delta method, the Fieller’s theorem, and the nonparametric bootstrap. We illustrate the methodologies on metabolic syndrome data collected from 4000 spousal pairs. Results: The bivariate Poisson model fitted the metabolic syndrome data quite satisfactorily. Moreover, the three methods of confidence interval estimation were almost identical, meaning that they have the same interval width.
文摘[Objectives]To reduce suicidal ideation and suicidal behavior through initial screening of patients with suicidal tendencies and implementing suicide prevention interventions during their hospitalization.[Methods]The Taihe Emotion-distress Index(THEI)was used to conduct pre-admission and post-discharge tests to explore the effects of suicide prevention measures during hospitalization on the alleviation of the disease and the reduction of suicidal behaviors.The study selected patients who were diagnosed with depression in the psychological outpatient department of Taihe Hospital from April 2019 to September 2019 and had to be hospitalized,including patients with moderate depressive episodes,severe depressive episodes with or without psychotic symptoms,and patients with suicidal thoughts and self-harming behaviors.[Results]The pre-admission and post-discharge test data of hospitalized patients were analyzed,and the non-parametric paired sample T test was carried out,and the result was P<0.05,showing that there are significant differences between the pre-admission and post-discharge test data.[Conclusions]The measures of suicide prevention intervention are effective to a certain extent.
文摘State is in the South East geopolitical zone of Nigeria. The major occupation of the people in this region is trading and farming, which depends on rainfall and other climatic factors. This paper presents statistical and trend analyses of the rainfall in some selected stations in Anambra State, which includes Ifite-Ogwari, Awka, Onitsha and Ihiala. Rainfall data for a period of 1971-2010 were obtained from Climate Research Unit (CRU). The existence of trend and statistical analyses was conducted on monthly total rainfalls using non-parametric techniques. The study revealed that overall averages of yearly and monthly total rainfall were 5798.78 mm and 1739.62 mm in Ifite-Ogwari, 6051.8 mm and 1815 mm in Awka, 6288.87 mm and 1886.88 mm in Onitsha, and 6637.19 mm and 1997.1 mm in Ihiala. Yearly total rainfall has Mann-Whitney of 26 and 41 between 1971 and 1990, 1991 and 2010 respectively in Ifite-Ogwari, 32 and 42 between 1971 and 1990, 1991 and 2010 respectively in Awka, 42 and 39 between 1971 and 1990, 1991 and 2010 respectively in Onitsha, and 33 and 45 between 1971 and 1990, 1991 and 2010 respectively in Ihiala. These parameters show that there are significant trends in the rainfall in term of yearly total for the period. Sen’s estimator revealed that there were significant downward trends for yearly total (-0.775 mm/year) and (-0.094 mm/year) within the period of 1971-1990 and 1991-2010 in Ifite-Ogwari. There was an upward trend of yearly total (1.841 mm/year) between 1971 and1990, whereas there was a downward trend of yearly total (-0.211) between 1991 and 2010 in Awka. It was concluded that there was a significant downward trend in the yearly total and mean rainfalls in Ifite-Ogwari, Awka, Onitsha and Ihiala in the last four decades (40 years), which could be attributed to climate change.
文摘The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.
