Plots a set of values against their spatially lagged values and gives the Moran coefficient as a measure of spatial autocorrelation.

```
moran_plot(
x,
w,
xlab = "x (centered)",
ylab = "Spatial Lag",
pch = 20,
col = "darkred",
size = 2,
alpha = 1,
lwd = 0.5,
na.rm = FALSE
)
```

## Source

Anselin, Luc. "Local indicators of spatial association—LISA." Geographical analysis 27, no. 2 (1995): 93-115.

## Arguments

- x
A numeric vector of length n.

- w
An n x n spatial connectivity matrix.

- xlab
Label for the x-axis.

- ylab
Label for the y-axis.

- pch
Symbol type.

- col
Symbol color.

- size
Symbol size.

- alpha
Symbol transparency.

- lwd
Width of the regression line.

- na.rm
If `na.rm = TRUE`

, any observations of `x`

with `NA`

values will be dropped from `x`

and from `w`

.

## Value

Returns a `gg`

plot, a scatter plot with `x`

on the horizontal and its spatially lagged values on the vertical axis (i.e. a Moran scatter plot).

## Details

For details on the symbol parameters see the documentation for geom_point.

If any observations with no neighbors are found (i.e. `any(Matrix::rowSums(w) == 0)`

) they will be dropped automatically and a message will print stating how many were dropped.

## Examples

```
data(georgia)
x <- georgia$income
w <- shape2mat(georgia, "W")
moran_plot(x, w)
```