Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Table 1.

The datasets of per capita GRP, level of urbanization, and the standardized residuals from linear squares regression of 29 Chinese regions (2012).

More »

Table 1 Expand

Fig 1.

The regression model of the linear relationship between urbanization and economic development of the 29 Chinese regions (2012).

More »

Fig 1 Expand

Fig 2.

The normalized scatterplot with a trendline of serial autocorrelation for the relationship between urbanization and economic development of the 29 Chinese regions (2012).

More »

Fig 2 Expand

Table 2.

The Durbin-Watson statistics, RCI values, and ARCI values of residual series from linear squares regression of 29 Chinese regions (2000–2012).

More »

Table 2 Expand

Fig 3.

The linear regression of the logistic relationship between urbanization and economic development of the 29 Chinese regions (2012).

More »

Fig 3 Expand

Table 3.

The coefficients and goodness of fit of the regression models of the correlation between urbanization and economic development of 29 Chinese regions (2000–2013).

More »

Table 3 Expand

Table 4.

The Durbin-Watson statistics, RCI values, and ARCI values of residual series from linearized logistic models of 29 Chinese regions (2000–2013).

More »

Table 4 Expand

Fig 4.

A flow chart of the two spatial autocorrelation approaches to testing residuals from least squares regression based on spatial random samples.

More »

Fig 4 Expand

Table 5.

The relationships between spatial contiguity functions and the definitions of contiguity.

More »

Table 5 Expand