The R package knnwtsim provides functions to implement k nearest neighbors (KNN) forecasting using a similarity metric tailored to the forecasting problem of predicting future observations of a response series where recent observations, seasonal or periodic patterns, and the values of one or more exogenous predictors all have predictive value in forecasting new response points. This paper will introduce the similarity measure of interest, and the functions in knnwtsim used to calculate, tune, and ultimately utilize it in KNN forecasting. This package may be of particular value in forecasting problems where the functional relationships between response and predictors are non-constant or piece-wise and thus can violate the assumptions of popular alternatives. In addition both real world and simulated time series datasets used in the development and testing of this approach have been made available with the package.

翻译：R 包件 knnwtsim 提供功能, 执行 k最近的邻居( KNN) 预报, 使用一个类似度量, 用于预测预测未来对最近观测、 季节性或周期性模式以及一个或多个外源预测器的值在预测新的响应点时都具有预测价值的反应系列的观测问题。 本文将介绍相似度度度, 以及 knwtsim 用于计算、 调制并最终在 KNN 预报中使用的函数 。 如果响应器和预测器之间的功能关系不固定或片断, 从而可能特别有助于预测问题, 从而可能违反流行替代物的假设。 此外, 软件包中还提供了在开发和测试这一方法中使用的真实世界和模拟时间序列数据集 。