Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” can be defined in many different dimensions. In a cross-section of nations, it can be defined using physical distance, cultural similarity, ecological similarity, or using frequency and intensity of interaction, such as trade relationships or enemy and ally relationships. Autocorrelation of regression residuals presents well-known problems in least-squares estimation, but autocorrelation also provides useful information for exploratory data analysis and model specification. The paper shows that autocorrelation is widespread in international datasets. The paper demonstrates the usefulness of autocorrelation in uncovering stylized facts about int...
Spatial autocorrelation is a phenomenon where the values of a variable located within certain geogra...
Autocorrelation, a common characteristic of many datasets, refers to correlation between values of t...
In the recent comparative literature the problem of simultaneously modeling func-tional and diffusio...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can...
Spatial autocorrelation may be defined as the relationship among values of a single variable that co...
Dow and Eff recently reported high levels of network autocorrelation for over eleven hundred and fif...
Spatial autocorrelation is an assessment of the correlation between two random variables which descr...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Many theories in political science predict the spatial clustering of similar behaviors among neighbo...
Abstract. A cross-product statistic is used to demonstrate that spatial interaction models are a spe...
Distinguishing the analysis of spatial data from classical analysis is only meaningful if the spati...
Spatial autocorrelation is a phenomenon where the values of a variable located within certain geogra...
Autocorrelation, a common characteristic of many datasets, refers to correlation between values of t...
In the recent comparative literature the problem of simultaneously modeling func-tional and diffusio...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate ” ca...
Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can...
Spatial autocorrelation may be defined as the relationship among values of a single variable that co...
Dow and Eff recently reported high levels of network autocorrelation for over eleven hundred and fif...
Spatial autocorrelation is an assessment of the correlation between two random variables which descr...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Classical statistical inference procedures usually assume the independence of sample units. However,...
Many theories in political science predict the spatial clustering of similar behaviors among neighbo...
Abstract. A cross-product statistic is used to demonstrate that spatial interaction models are a spe...
Distinguishing the analysis of spatial data from classical analysis is only meaningful if the spati...
Spatial autocorrelation is a phenomenon where the values of a variable located within certain geogra...
Autocorrelation, a common characteristic of many datasets, refers to correlation between values of t...
In the recent comparative literature the problem of simultaneously modeling func-tional and diffusio...