config.json

{
  "keywords": [],
  "export": [
    "arma.json"
  ],
  "时间序列": {
    "keywords": [],
    "children": [
      {
        "时间序列基础": {
          "keywords": [],
          "children": [
            {
              "含有重复索引的时间序列": {
                "keywords": [],
                "children": []
              }
            }
          ]
        }
      },
      {
        "时区处理": {
          "keywords": [],
          "children": [
            {
              "时区的本地化和转换": {
                "keywords": [],
                "children": []
              }
            },
            {
              "时区感知时间戳对象的操作": {
                "keywords": [],
                "children": []
              }
            },
            {
              "不同时区间的操作": {
                "keywords": [],
                "children": []
              }
            }
          ]
        }
      },
      {
        "时间区间和区间算术": {
          "keywords": [],
          "children": [
            {
              "区间频率转换": {
                "keywords": [],
                "children": []
              }
            },
            {
              "季度区间频率": {
                "keywords": [],
                "children": []
              }
            },
            {
              "将时间戳转换为区间（以及逆转换）": {
                "keywords": [],
                "children": []
              }
            },
            {
              "从数组生成PeriodIndex": {
                "keywords": [],
                "children": []
              }
            }
          ]
        }
      },
      {
        "重新采样与频率转换": {
          "keywords": [],
          "children": [
            {
              "向下采样": {
                "keywords": [],
                "children": []
              }
            },
            {
              "向上采样与插值": {
                "keywords": [],
                "children": []
              }
            },
            {
              "使用区间进行重新采样": {
                "keywords": [],
                "children": []
              }
            }
          ]
        }
      },
      {
        "移动窗口函数": {
          "keywords": [],
          "children": [
            {
              "指数加权函数": {
                "keywords": [],
                "children": []
              }
            },
            {
              "二元移动窗口函数": {
                "keywords": [],
                "children": []
              }
            },
            {
              "用户自定义的移动窗口函数": {
                "keywords": [],
                "children": []
              }
            }
          ]
        }
      }
    ]
  },
  "node_id": "python-3-241",
  "children": [
    {
      "变化的分类": {
        "keywords": [],
        "children": [],
        "node_id": "python-4-1402"
      }
    },
    {
      "包含趋势的序列分析": {
        "keywords": [],
        "children": [
          {
            "曲线拟合": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1324"
            }
          },
          {
            "从时间序列中去除趋势": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1325"
            }
          }
        ],
        "node_id": "python-4-1403"
      }
    },
    {
      "包含周期性的序列数据分析": {
        "keywords": [],
        "children": [],
        "node_id": "python-4-1404"
      }
    },
    {
      "从时间序列中去除周期性": {
        "keywords": [],
        "children": [
          {
            "滤波": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1326"
            }
          },
          {
            "差分": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1327"
            }
          }
        ],
        "node_id": "python-4-1405"
      }
    },
    {
      "平稳时间序列": {
        "keywords": [],
        "children": [
          {
            "平稳过程": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1328"
            }
          },
          {
            "自相关和相关图": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1329"
            }
          },
          {
            "自协方差和自相关函数的估计": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1330"
            }
          }
        ],
        "node_id": "python-4-1406"
      }
    },
    {
      "使用Python进行时间序列分析": {
        "keywords": [],
        "children": [
          {
            "有用的方法": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1331"
            }
          },
          {
            "自回归过程": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1332"
            }
          },
          {
            "估计AR过程的参数": {
              "keywords": [],
              "children": [],
              "node_id": "python-5-1333"
            }
          }
        ],
        "node_id": "python-4-1407"
      }
    },
    {
      "混合ARMA模型": {
        "keywords": [],
        "children": [],
        "node_id": "python-4-1408"
      }
    },
    {
      "集成ARMA模型": {
        "keywords": [],
        "children": [],
        "node_id": "python-4-1409"
      }
    },
    {
      "一个特殊的场景": {
        "keywords": [],
        "children": [],
        "node_id": "python-4-1410"
      }
    },
    {
      "数据缺失": {
        "keywords": [],
        "children": [],
        "node_id": "python-4-1411"
      }
    }
  ]
}