Temporal lags in observed and dark diversity in the Anthropocene

2020 ◽  
Vol 26 (6) ◽  
pp. 3193-3201 ◽  
Author(s):  
Diego P. F. Trindade ◽  
Carlos P. Carmona ◽  
Meelis Pärtel
Keyword(s):  
Temporal Lags

scholarly journals Adaptation to motor-visual and motor-auditory temporal lags transfer across modalities

2009 ◽  
Vol 201 (3) ◽  
pp. 393-399 ◽  
Author(s):  
Yoshimori Sugano ◽  
Mirjam Keetels ◽  
Jean Vroomen
Keyword(s):  
Temporal Lags

scholarly journals Measuring Temporal Lags in Delay-Tolerant Networks

2014 ◽  
Vol 63 (2) ◽  
pp. 397-410 ◽  
Author(s):  
Arnaud Casteigts ◽  
Paola Flocchini ◽  
Bernard Mans ◽  
Nicola Santoro
Keyword(s):  
Delay Tolerant Networks ◽  
Delay Tolerant ◽  
Temporal Lags

scholarly journals Relação entre a precipitação do leste do Nordeste do Brasil e a temperatura dos oceanos

2009 ◽  
Vol 13 (4) ◽  
pp. 462-469 ◽  
Author(s):  
Geber B. de A. Moura ◽  
José O. R. de Aragão ◽  
José S. P. de Melo ◽  
Ana P. N. da Silva ◽  
Pedro R. Giongo ◽  
...  
Keyword(s):  
Temporal Lags

O objetivo deste trabalho foi correlacionar a precipitação (março a julho) de um grupo de postos homogêneos do setor leste do Nordeste do Brasil (NEB) com Anomalia de Temperatura da Superfície do Mar (ATSM) e identificar áreas de influência deste parâmetro nas chuvas da região. O período de estudo foi de 1945 a 1985 e a análise mostrou influência do Atlântico e Pacífico sobre as chuvas do setor leste, sendo a correlação do Atlântico maior, principalmente na área do Dipolo (correlação maior que 0,6, significativa a p < 0,05). Os modos zonal e meridional, descritos por Servain & Arnault (1995) foram detectados durante análises feitas com defasagem temporal ("lags"). No Oceano Pacífico Tropical Leste se encontrou correlações negativas indicando a presença dos ramos descendentes da célula de Walker no setor leste do NEB.

Temporal Lags in Comparative Retailing

1972 ◽  
Vol 36 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Johan Arndt
Keyword(s):  
Environmental Factors ◽  
Temporal Lags

Is the structure of a retailing system dependent upon selected characteristics of the country served? The author's evidence affirms this hypothesis. The results reported may have important strategic implications for multinational retailers by serving as a base for forecasting. Temporal lags in the development of retail systems are found to approach the same length as lags in certain environmental factors.

scholarly journals How to Deal With Reverse Causality Using Panel Data? Recommendations for Researchers Based on a Simulation Study

2019 ◽  
pp. 004912411988247 ◽  
Author(s):  
Lars Leszczensky ◽  
Tobias Wolbring
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Reverse Causality ◽  
Social Scientists ◽  
Panel Models ◽  
Panel Model ◽  
Wide Range ◽  
Causal Ordering ◽  
Alternative Solutions ◽  
Temporal Lags

Does X affect Y? Answering this question is particularly difficult if reverse causality is looming. Many social scientists turn to panel data to address such questions of causal ordering. Yet even in longitudinal analyses, reverse causality threatens causal inference based on conventional panel models. Whereas the methodological literature has suggested various alternative solutions, these approaches face many criticisms, chief among them to be sensitive to the correct specification of temporal lags. Applied researchers are thus left with little guidance. Seeking to provide such guidance, we compare how different panel models perform under a range of different conditions. Our Monte Carlo simulations reveal that unlike conventional panel models, a cross-lagged panel model with fixed effects not only offers protection against bias arising from reverse causality under a wide range of conditions but also helps to circumvent the problem of misspecified temporal lags.

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