input: Write a python function to analyze the sentiment of a given sentence using NLTK's VADER sentiment analyzer.
  assert analyze_sentiment('I love this product, it is amazing!')=='positive'
  assert analyze_sentiment('This is the worst experience ever.')=='negative'
  assert analyze_sentiment('It is an average day.')=='neutral'
output: def analyze_sentiment(sentence):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon')
      
      sid = SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(sentence)
      
      if scores['compound'] >= 0.05:
          return 'positive'
      elif scores['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'