code: def estimateTrends(self):
      self.mTime = self.mTimeInfo.mTime
      self.mSignal = self.mTimeInfo.mSignal
      self.mTrendFrame = pd.DataFrame()
      self.mTimeInfo.addVars(self.mTrendFrame)
      for trend in self.mTrendList:
          trend.mOptions = self.mOptions
          trend.fit()
          if trend.mOptions.mDebugPerformance:
              trend.computePerf()
          self.mTrendFrame[trend.mOutName] = trend.mTrendFrame[
              trend.mOutName
          ]
          self.mTrendFrame[
              trend.mOutName + "_residue"
          ] = trend.mTrendFrame[trend.mOutName + "_residue"]
          if self.mOptions.mDebug:
              self.check_residue(
                  self.mTrendFrame[trend.mOutName + "_residue"].values,
                  trend.mOutName + "_residue",
              )
      pass
  
imports: import pandas
  import numpy
  from .None import Time
  from .None import Perf
  from .None import Plots
  from .None import Utils
  import sklearn
  import sklearn.preprocessing
  import sklearn.linear_model
  from sklearn.feature_selection import RFE
  from sklearn.linear_model import LinearRegression
label_desc: Use image node_id 7 for calling the cTrendEstimator obj's underlying member method code with example usage: obj.estimateTrends() without return types