class_docstr: 1D Kernel Density Regression/Kernel Smoother
  
  Requires:
  x - array_like of x values
  y - array_like of y values
  Kernel - Kernel object, Default is Gaussian.
class_docstr_tok: ["1D","Kernel","Density","Regression\/Kernel","Smoother","Requires",":","x","-","array_like","of","x","values","y","-","array_like","of","y","values","Kernel","-","Kernel","object",",","Default","is","Gaussian","."]
code: def std(self, x):
      return np.sqrt(self.var(x))
  
file_path: statsmodels/statsmodels/sandbox/nonparametric/smoothers.py
imports: import numpy
  from .None import kernels
label_desc: Use image node_id 7 for calling the KernelSmoother obj's underlying member method code with example usage: obj.std(x) and returns: np