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docs vmanomaly fix anchor

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Signed-off-by: Artem Navoiev <tenmozes@gmail.com>
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docs/anomaly-detection/components/models.md
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@ -41,7 +41,7 @@ VM Anomaly Detection (`vmanomaly` hereinafter) models support 2 groups of parame
* [Seasonal Trend Decomposition](#seasonal-trend-decomposition) - similarly to Holt-Winters, is best for **data with pronounced [seasonal](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-1/#seasonality) and [trend](https://victoriametrics.com/blog/victoriametrics-anomaly-detection-handbook-chapter-1/#trend) components**
* [ARIMA](#arima) - use when your data shows **clear patterns or autocorrelation (the degree of correlation between values of the same series at different periods)**. However, good understanding of machine learning is required to tune.
* [Isolation forest (Multivariate)](#isolation-forest-multivariate) - useful for **metrics data interaction** (several queries/metrics -> single anomaly score) and **efficient in detecting anomalies in high-dimensional datasets**
* [Custom model](#custom-model) - benefit from your own models and expertise to better support your **unique use case**.
* [Custom model](#custom-model-guide) - benefit from your own models and expertise to better support your **unique use case**.
### [Prophet](https://facebook.github.io/prophet/)