نتایج جستجو برای: modern spatial statistics method such as spatial auto correlation global moran

تعداد نتایج: 7396464  

Journal: :مدیریت خاک و تولید پایدار 0
فهیمه خرمی زاده انجمن علوم خاک ایران ناصر دواتگر استادیار پژوهش و ریاست موسسه تحقیقات برنج کشور/ موسسه تحقیقات برنج کشور محمد مهدی طهرانی استادیارپژوهش، گروه خاکشناسی/ مؤسسه تحقیقات خاک و آب کرج وحیدرضا قاسمی دهکردی استادیارپژوهش، گروه خاکشناسی/ مؤسسه تحقیقات خاک و آب کرج ابراهیم اسعدی اسکویی کارشناس ارشد هواشناسی کشاورزی/ اداره هواشناسی گیلان

iron is an essential nutrients in rice. accurate assessment of this element in paddy soils is very important. improving fertility management, accurate interpolation, being aware of spatial variability and patterns of distribution of micronutrients are the most important factors in soil management and accurate consumption of fertilizers. this study was done for investigating of available iron, d...

2017
Mellina YAMAMURA Marcelino SANTOS NETO Francisco CHIARAVALLOTI NETO Luiz Henrique ARROYO Antônio Carlos Vieira RAMOS Ana Angélica Rêgo de QUEIROZ Aylana de Souza BELCHIOR Danielle Talita dos SANTOS Juliane de Almeida CRISPIM Ione Carvalho PINTO Severina Alice da Costa UCHÔA Regina Célia FIORATI Ricardo Alexandre ARCÊNCIO

BACKGROUND In Brazil, people still fall ill and die from tuberculosis (TB), and this can be explained by the significant impasse in the equity of distribution of therapeutic resources to the population as a whole. The aim was to identify geographical areas which have shown progress in terms of equity (of income, schooling and urban occupancy) and test its effect on mortality from TB in a munici...

ژورنال: اندیشه آماری 2021

Spatial count data is usually found in most sciences such as environmental science, meteorology, geology and medicine. Spatial generalized linear models based on poisson (poisson-lognormal spatial model) and binomial (binomial-logitnormal spatial model) distributions are often used to analyze discrete count data in which spatial correlation is observed. The likelihood function of these models i...

2006
Rasmus P. Waagepetersen

We summarize and discuss the current state of spatial point process theory and directions for future research, making an analogy with generalized linear models and random effect models, and illustrating the theory with various examples of applications. In particular, we consider Poisson, Gibbs, and Cox process models, diagnostic tools and model checking, Markov chain Monte Carlo algorithms, com...

Journal: :Sao Paulo medical journal = Revista paulista de medicina 2014
Milena Cristina da Silva Almeida Camila de Moraes Santos Gomes Luiz Fernando Costa Nascimento

CONTEXT AND OBJECTIVE Alzheimer's disease is a common cause of dementia and identifying possible spatial patterns of mortality due to this disease may enable preventive actions. The objective of this study was to identify spatial distribution patterns of mortality due to Alzheimer's disease in the state of São Paulo. DESIGN AND SETTING Ecological and exploratory study conducted in all municip...

Journal: :Cadernos de saude publica 2001
O L Neto M B Barros C M Martelli S A Silva S M Cavenaghi J B Siqueira

The aim of this study was to investigate the spatial pattern of neonatal and post-neonatal mortality in the city of Goiânia, Central Brazil. Analyses were based on linked birth and death certificates relating to 101,000 in-hospital live births from mothers residing in the city of Goiânia over the 1992-1996 period. Overall neonatal and post-neonatal mortality probabilities were calculated using ...

Background & Aims of the Study: The aim of this study is spatial distribution of arsenic (As) under the influence of chemical fertilizers using geostatistics in city of Eghlid, Iran. Materials & Methods: In this descriptive study, spatial distribution of arsenic was randomly investigated in 100 soil samples and its content was measured by ICP-OES. Spatial distribution of As and geostatistic...

2003
Pusheng Zhang Shashi Shekhar Vipin Kumar Yan Huang

A spatial time series dataset [18, 19] is a collection of time series [3], each referencing a location in a common spatial framework [17]. Finding highly correlated time series from spatial time series datasets collected by satellites, sensor nets, retailers, mobile device servers, and medical instruments on a daily basis is important for many application domains such as epidemiology, ecology, ...

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