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Evidence row 2201178

Observed , by sync.x402_bazaar/1.

Kind
listing
About
source_record x402_bazaar:https://time-series-calc.x402tookit.com/exponential-smoothing
Recorded
Previous row
None: the first of its kind about this subject
Body SHA-256
eff4d441eefc2455197c7de60fc252551f0f777cf8bbb52d3cb15520807a8e9e
Leaf
0x3df8569968648dc1cc6b438e3f4a65c637d3a11bafc1d50037663f1afcc62498

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://time-series-calc.x402tookit.com/exponential-smoothing"
    ]
  ],
  "name": "Time Series Calculators",
  "owner_address": "0xb531320805c5bed1d46aeadcf4f008fdf172dbda",
  "raw": {
    "accepts": [
      {
        "amount": "30000",
        "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 300,
        "network": "eip155:8453",
        "payTo": "0xb531320805C5BED1D46AEaDcF4F008FDF172DBDa",
        "scheme": "exact"
      },
      {
        "amount": "30000",
        "asset": "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",
        "extra": {
          "feePayer": "D6ZhtNQ5nT9ZnTHUbqXZsTx5MH2rPFiBBggX4hY1WePM",
          "transactionVersions": [
            0
          ]
        },
        "maxTimeoutSeconds": 300,
        "network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
        "payTo": "DUPiupXtuox38dcGoXUKer5mAydCzmaHjrbQ66qeEm8s",
        "scheme": "exact"
      },
      {
        "amount": "30000",
        "asset": "0x3c499c542cEF5E3811e1192ce70d8cC03d5c3359",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 300,
        "network": "eip155:137",
        "payTo": "0xb531320805C5BED1D46AEaDcF4F008FDF172DBDa",
        "scheme": "exact"
      },
      {
        "amount": "30000",
        "asset": "0xaf88d065e77c8cC2239327C5EDb3A432268e5831",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 300,
        "network": "eip155:42161",
        "payTo": "0xb531320805C5BED1D46AEaDcF4F008FDF172DBDa",
        "scheme": "exact"
      }
    ],
    "description": "Simple, Holt trend or Holt-Winters seasonal exponential smoothing with a forecast h steps ahead and in-sample fit error.",
    "extensions": {
      "bazaar": {
        "info": {
          "input": {
            "method": "GET",
            "queryParams": {
              "alpha": 0.5,
              "beta": 0.3,
              "horizon": 3,
              "method": "holt",
              "values": "10,12,11,13,15,14,16,18"
            },
            "type": "http"
          },
          "output": {
            "example": {
              "alpha": 0.5,
              "asOf": "2026-10-21T06:18:22.423Z",
              "beta": 0.3,
              "degraded": false,
              "disclaimer": "Screening signal computed from the named public source. Not financial, legal or investment advice; provided as is. Verify at the source before acting.",
              "finalLevel": 17.5657908,
              "finalTrend": 1.14577245,
              "fitted": [
                null,
                12
              ],
              "fittedCount": 7,
              "forecast": [
                18.7115632,
                19.8573357
              ],
              "gamma": null,
              "horizon": 3,
              "inSampleMae": 1.08524103,
              "inSampleRmse": 1.53548832,
              "inSampleSse": 16.5040707,
              "method": "holt",
              "notChecked": [
                "parameter optimisation (alpha, beta, gamma are used exactly as given)",
                "prediction intervals",
                "…1 more"
              ],
              "reasons": [
                "Level starts at the first value and trend at (second - first); fitted values begin at position 2.",
                "Forecasts use the final state only. Parameters are as given, not optimised.",
                "…1 more"
              ],
              "seasonLength": null,
              "seasonalIndices": null,
              "source": "computed locally (Hyndman and Athanasopoulos, Forecasting: Principles and Practice, exponential smoothing methods)",
              "summary": "holt smoothing: forecast 3 steps ahead starts at 18.7116; in-sample RMSE 1.535.",
              "verdict": "COMPUTED"
            },
            "type": "json"
          }
        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "method": {
                  "enum": [
                    "GET"
                  ],
                  "type": "string"
                },
                "queryParams": {
                  "properties": {
                    "alpha": {
                      "description": "Level smoothing 0 to 1 exclusive of 0 (default 0.3)",
                      "type": "number"
                    },
                    "beta": {
                      "description": "Trend smoothing 0 to 1 (default 0.1; holt and hw only)",
                      "type": "number"
                    },
                    "gamma": {
                      "description": "Seasonal smoothing 0 to 1 (default 0.1; hw only)",
                      "type": "number"
                    },
                    "horizon": {
                      "description": "Steps to forecast, 1 to 100 (default 3)",
                      "type": "integer"
                    },
                    "method": {
                      "description": "simple, holt, hw-additive or hw-multiplicative (default simple)",
                      "type": "string"
                    },
                    "seasonLength": {
                      "description": "Observations per season, 2 or more (required for hw; needs 2 full seasons of data)",
                      "type": "integer"
                    },
                    "values": {
                      "description": "Comma-separated numbers in time order, oldest first (2 to 500), any one unit",
                      "type": "string"
                    }
                  },
                  "required": [
                    "values"
                  ],
                  "type": "object"
                },
                "type": {
                  "const": "http",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "method"
              ],
              "type": "object"
            },
            "output": {
              "properties": {
                "example": {
                  "properties": {
                    "alpha": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "asOf": {
                      "type": [
                        "null",
                        "string"
                      ]
                    },
                    "beta": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "degraded": {
                      "type": [
                        "boolean",
                        "null"
                      ]
                    },
                    "disclaimer": {
                      "type": [
                        "null",
                        "string"
                      ]
                    },
                    "finalLevel": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "finalTrend": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "fitted": {
                      "items": {
                        "type": [
                          "null",
                          "number"
                        ]
                      },
                      "type": [
                        "array",
                        "null"
                      ]
                    },
                    "fittedCount": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "forecast": {
                      "items": {
                        "type": "number"
                      },
                      "type": [
                        "array",
                        "null"
                      ]
                    },
                    "gamma": {},
                    "horizon": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "inSampleMae": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "inSampleRmse": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "inSampleSse": {
                      "type": [
                        "null",
                        "number"
                      ]
                    },
                    "method": {
                      "type": [
                        "null",
                        "string"
                      ]
                    },
                    "notChecked": {
                      "items": {
                        "type": "string"
                      },
                      "type": [
                        "array",
                        "null"
                      ]
                    },
                    "reasons": {
                      "items": {
                        "type": "string"
                      },
                      "type": [
                        "array",
                        "null"
                      ]
                    },
                    "seasonLength": {},
                    "seasonalIndices": {},
                    "source": {
                      "type": [
                        "null",
                        "string"
                      ]
                    },
                    "summary": {
                      "type": [
                        "null",
                        "string"
                      ]
                    },
                    "verdict": {
                      "type": [
                        "null",
                        "string"
                      ]
                    }
                  },
                  "type": "object"
                },
                "type": {
                  "type": "string"
                }
              },
              "required": [
                "type"
              ],
              "type": "object"
            }
          },
          "required": [
            "input"
          ],
          "type": "object"
        }
      }
    },
    "lastUpdated": "2026-11-02T04:09:43.739Z",
    "quality": {
      "l30DaysTotalCalls": 1,
      "l30DaysUniquePayers": 1,
      "lastCalledAt": "2026-11-02T04:09:43.506Z"
    },
    "resource": "https://time-series-calc.x402tookit.com/exponential-smoothing",
    "serviceName": "Time Series Calculators",
    "tags": [
      "exponential-smoothing",
      "forecast",
      "holt-winters",
      "time-series"
    ],
    "type": "http",
    "x402Version": 2
  },
  "source": "x402_bazaar",
  "summary": "Simple, Holt trend or Holt-Winters seasonal exponential smoothing with a forecast h steps ahead and in-sample fit error."
}

What the leaf hashes

{"body":"eff4d441eefc2455197c7de60fc252551f0f777cf8bbb52d3cb15520807a8e9e","id":2201178,"kind":"listing","method":"sync.x402_bazaar/1","observed_us":1793646801193704,"prev":null,"subject":"x402_bazaar:https://time-series-calc.x402tookit.com/exponential-smoothing","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (444186 rows).

  1. 0x3df880b138d212f8d618d1b34218eccc226fef72c07d9dd3280cf063627d09a3
  2. 0x2cfb8f9e1bfbfcc0f6038b0552fcb6abd3da2a76159a22077645d9194f8eeb6a
  3. 0xc3a827c705bf82b1498d44d1e58c3915666899ac91c41858bd517194e97ef143
  4. 0x82ae6d56375068722c21f0a5b606f18c71115bbec998d0bdcabde17de7d8629a
  5. 0x948f36f834c314c95aa314e8a4e449d57e9ddcf507161b2f43d9cf77d3c9de57
  6. 0xf55c2e8a8b0659cde46960c5491e2b9ac3429ba26b39a84b19385399ddc29470
  7. 0x6d6c39bf4df06a9ed7b13ac353a3a4ff158c443ab29ec1ee66180e4c5baaba64
  8. 0x4d2edcc2dc5f6ca14b7928b1faaee55c2127b4e0e69e6e30fdcdcc71a6febb06
  9. 0x55d5da242fc4b204f44bf3af14af7eae4c6a3395c2ab92f18498213812a1098c
  10. 0x0093a9f56bed29515e4c952c8636a7899fdd721726c104eaf5aa0481bcf1d5d2
  11. 0xd6359ca2c1e268b80cbd6a1a39e7bf31cc48f7cc2c0c7ca155d42f73229b2dba
  12. 0xb1c944b99390ba5175965090f5362380c7485dc911c281e22b9c18263ec8c4ed
  13. 0x361907c755dedca0a2adf05840c4c503b2c9a3af060e2659c8c63c2a1e438de2
  14. 0x2205fefa1140121f3fe567e386a9612e8f7236f2a6b4c18d07e5fc4d08bd90e5
  15. 0x8448bd1fe3c2d48b62a118ace4a5cb82fee53586dd43d776c2526ad844398919
  16. 0x8760c227928c5295506cd8606e763f86cf8cd2a549820fab4dc86d29ca0d816d
  17. 0xa20b9be86af7d690e040c9060a373b2fc5498edf3432f43c26f74fa2febc1e9a
  18. 0x050f2978b537f7afb21ee1551577cdf146d1c56f4df12d24315ae5e69366b0a4
  19. 0x365b161a4b68d750dcc4b3ecce1154a2163c87b08762079428e68f0ebb6a754e
Day root
0x78fecaabbe319e56f5c4b80fc02e2052e198ad24781da8832a475ff65f2002d1
Chained
0xdc35957db5d1371ca382b9152878ffece28ec7c5cb4f98fd71ddb367f8b999b2
Published
On Arc Testnet, block 70432815: 0x56b814612eb2e3e544153df3e91e1f7199106d1e430c7d8c6b653feeb9ebe9af

How to check it · This row as JSON