class_docstr: Base class for multivariate kernels.
  
  An instance of MultivariateKernel implements a `call` method having
  signature `call(x, loc)`, returning the kernel weights comparing `x`
  (a 1d ndarray) to each row of `loc` (a 2d ndarray).
docstr: Set the bandwidth to the given vector.
  
  Parameters
  ----------
  bw : array_like
      A vector of non-negative bandwidth values.
docstr_tok: ["Set","the","bandwidth","to","the","given","vector",".","Parameters","--","--","--","--","--","bw",":","array_like","A","vector","of","non-negative","bandwidth","values","."]
code: def set_bandwidth(self, bw):
      """
      Set the bandwidth to the given vector.
  
      Parameters
      ----------
      bw : array_like
          A vector of non-negative bandwidth values.
      """
  
      self.bw = bw
      self._setup()
  
imports: import numpy
  import scipy.sparse
  from scipy.sparse.linalg import svds
  from scipy.optimize import fminbound
  import warnings
  from statsmodels.tools.tools import Bunch
  from statsmodels.tools.sm_exceptions import IterationLimitWarning, iteration_limit_doc
label_desc: Use image node_id 2 for calling the MultivariateKernel obj's underlying member method code with example usage: obj.set_bandwidth(bw) without return types