空间核密度估计中无条件核密度估计、空间动态核密度估计和空间静态核密度估计可实现的matlab代码

以下是空间核密度估计中三种方法的Matlab代码示例：

1. 无条件核密度估计：

% 生成数据
x = randn(100, 1);
y = randn(100, 1);

% 设置网格
gridx = linspace(min(x), max(x), 100);
gridy = linspace(min(y), max(y), 100);
[X, Y] = meshgrid(gridx, gridy);

% 计算无条件核密度估计
[f, xi] = ksdensity([x, y], 'support', [gridx(:), gridy(:)], 'function', 'pdf');
f = reshape(f, length(gridy), length(gridx));

% 绘制结果
figure;
contourf(X, Y, f, 'LineStyle', 'none');
colorbar;

2. 空间动态核密度估计：

% 生成数据
x = randn(100, 1);
y = randn(100, 1);

% 设置网格
gridx = linspace(min(x), max(x), 100);
gridy = linspace(min(y), max(y), 100);
[X, Y] = meshgrid(gridx, gridy);

% 计算距离矩阵
D = pdist2([x, y], [x, y]);

% 计算空间动态核密度估计
h = 0.5;  % 带宽参数
f = zeros(length(gridy), length(gridx));
for i = 1:length(x)
    K = exp(-D(i, :).^2 / (2 * h^2));
    f = f + K' * K;
end
f = f / (length(x) * h^2 * pi);

% 绘制结果
figure;
contourf(X, Y, f, 'LineStyle', 'none');
colorbar;

3. 空间静态核密度估计：

% 生成数据
x = randn(100, 1);
y = randn(100, 1);

% 设置网格
gridx = linspace(min(x), max(x), 100);
gridy = linspace(min(y), max(y), 100);
[X, Y] = meshgrid(gridx, gridy);

% 计算空间静态核密度估计
h = 0.5;  % 带宽参数
f = zeros(length(gridy), length(gridx));
for i = 1:length(x)
    Kx = normpdf((X - x(i)) / h);
    Ky = normpdf((Y - y(i)) / h);
    f = f + Kx' * Ky;
end
f = f / (length(x) * h^2 * pi);

% 绘制结果
figure;
contourf(X, Y, f, 'LineStyle', 'none');
colorbar;