我有一个包含日期、ID、变量和值的数据框。我想比较代表系列较低点的点。数据代表潮汐。我想找到方法，以便比较低潮点。
玩具数据如下：
jd1 <- structure(list(Date = c(300.0416565, 300.0833435, 300.125, 300.1666565,
300.2083435, 300.25, 300.2916565, 300.3333435, 300.375, 300.4166565,
300.4583435, 300.5, 300.5416565, 300.5833435, 300.625, 300.6666565,
300.7083435, 300.75, 300.7916565, 300.8333435, 300.875, 300.9166565,
300.9583435, 301, 301.0416565, 301.0833435, 301.125, 301.1666565,
301.2083435, 301.25, 301.2916565, 301.3333435, 301.375, 301.4166565,
301.4583435, 301.5, 301.5416565, 301.5833435, 301.625, 301.6666565,
301.7083435, 301.75, 301.7916565, 301.8333435, 301.875, 301.9166565,
301.9583435, 302, 302.0416565, 302.0833435, 302.125, 302.1666565,
302.2083435, 302.25, 302.2916565, 302.3333435, 302.375, 302.4166565,
302.4583435, 302.5, 302.5416565, 302.5833435, 302.625, 302.6666565,
302.7083435, 302.75, 302.7916565, 302.8333435, 302.875, 302.9166565,
302.9583435, 303, 303.0416565, 303.0833435, 303.125, 303.1666565,
303.2083435, 303.25, 303.2916565, 303.3333435, 303.375, 303.4166565,
303.4583435, 303.5, 303.5416565, 303.5833435, 303.625, 303.6666565,
303.7083435, 303.75, 303.7916565, 303.8333435, 303.875, 303.9166565,
303.9583435, 304, 304.0416565, 304.0833435, 304.125, 304.1666565,
304.2083435, 304.25, 304.2916565, 304.3333435, 304.375, 304.4166565,
304.4583435, 304.5, 304.5416565, 304.5833435, 304.625, 304.6666565,
304.7083435, 304.75, 304.7916565, 304.8333435, 304.875, 304.9166565,
304.9583435, 300.0416565, 300.0833435, 300.125, 300.1666565,
300.2083435, 300.25, 300.2916565, 300.3333435, 300.375, 300.4166565,
300.4583435, 300.5, 300.5416565, 300.5833435, 300.625, 300.6666565,
300.7083435, 300.75, 300.7916565, 300.8333435, 300.875, 300.9166565,
300.9583435, 301, 301.0416565, 301.0833435, 301.125, 301.1666565,
301.2083435, 301.25, 301.2916565, 301.3333435, 301.375, 301.4166565,
301.4583435, 301.5, 301.5416565, 301.5833435, 301.625, 301.6666565,
301.7083435, 301.75, 301.7916565, 301.8333435, 301.875, 301.9166565,
301.9583435, 302, 302.0416565, 302.0833435, 302.125, 302.1666565,
302.2083435, 302.25, 302.2916565, 302.3333435, 302.375, 302.4166565,
302.4583435, 302.5, 302.5416565, 302.5833435, 302.625, 302.6666565,
302.7083435, 302.75, 302.7916565, 302.8333435, 302.875, 302.9166565,
302.9583435, 303, 303.0416565, 303.0833435, 303.125, 303.1666565,
303.2083435, 303.25, 303.2916565, 303.3333435, 303.375, 303.4166565,
303.4583435, 303.5, 303.5416565, 303.5833435, 303.625, 303.6666565,
303.7083435, 303.75, 303.7916565, 303.8333435, 303.875, 303.9166565,
303.9583435, 304, 304.0416565, 304.0833435, 304.125, 304.1666565,
304.2083435, 304.25, 304.2916565, 304.3333435, 304.375, 304.4166565,
304.4583435, 304.5, 304.5416565, 304.5833435, 304.625, 304.6666565,
304.7083435, 304.75, 304.7916565, 304.8333435, 304.875, 304.9166565,
304.9583435, 300.0416565, 300.0833435, 300.125, 300.1666565,
300.2083435, 300.25, 300.2916565, 300.3333435, 300.375, 300.4166565,
300.4583435, 300.5, 300.5416565, 300.5833435, 300.625, 300.6666565,
300.7083435, 300.75, 300.7916565, 300.8333435, 300.875, 300.9166565,
300.9583435, 301, 301.0416565, 301.0833435, 301.125, 301.1666565,
301.2083435, 301.25, 301.2916565, 301.3333435, 301.375, 301.4166565,
301.4583435, 301.5, 301.5416565, 301.5833435, 301.625, 301.6666565,
301.7083435, 301.75, 301.7916565, 301.8333435, 301.875, 301.9166565,
301.9583435, 302, 302.0416565, 302.0833435, 302.125, 302.1666565,
302.2083435, 302.25, 302.2916565, 302.3333435, 302.375, 302.4166565,
302.4583435, 302.5, 302.5416565, 302.5833435, 302.625, 302.6666565,
302.7083435, 302.75, 302.7916565, 302.8333435, 302.875, 302.9166565,
302.9583435, 303, 303.0416565, 303.0833435, 303.125, 303.1666565,
303.2083435, 303.25, 303.2916565, 303.3333435, 303.375, 303.4166565,
303.4583435, 303.5, 303.5416565, 303.5833435, 303.625, 303.6666565,
303.7083435, 303.75, 303.7916565, 303.8333435, 303.875, 303.9166565,
303.9583435, 304, 304.0416565, 304.0833435, 304.125, 304.1666565,
304.2083435, 304.25, 304.2916565, 304.3333435, 304.375, 304.4166565,
304.4583435, 304.5, 304.5416565, 304.5833435, 304.625, 304.6666565,
304.7083435, 304.75, 304.7916565, 304.8333435, 304.875, 304.9166565,
304.9583435, 300.0416565, 300.0833435, 300.125, 300.1666565,
300.2083435, 300.25, 300.2916565, 300.3333435, 300.375, 300.4166565,
300.4583435, 300.5, 300.5416565, 300.5833435, 300.625, 300.6666565,
300.7083435, 300.75, 300.7916565, 300.8333435, 300.875, 300.9166565,
300.9583435, 301, 301.0416565, 301.0833435, 301.125, 301.1666565,
301.2083435, 301.25, 301.2916565, 301.3333435, 301.375, 301.4166565,
301.4583435, 301.5, 301.5416565, 301.5833435, 301.625, 301.6666565,
301.7083435, 301.75, 301.7916565, 301.8333435, 301.875, 301.9166565,
301.9583435, 302, 302.0416565, 302.0833435, 302.125, 302.1666565,
302.2083435, 302.25, 302.2916565, 302.3333435, 302.375, 302.4166565,
302.4583435, 302.5, 302.5416565, 302.5833435, 302.625, 302.6666565,
302.7083435, 302.75, 302.7916565, 302.8333435, 302.875, 302.9166565,
302.9583435, 303, 303.0416565, 303.0833435, 303.125, 303.1666565,
303.2083435, 303.25, 303.2916565, 303.3333435, 303.375, 303.4166565,
303.4583435, 303.5, 303.5416565, 303.5833435, 303.625, 303.6666565,
303.7083435, 303.75, 303.7916565, 303.8333435, 303.875, 303.9166565,
303.9583435, 304, 304.0416565, 304.0833435, 304.125, 304.1666565,
304.2083435, 304.25, 304.2916565, 304.3333435, 304.375, 304.4166565,
304.4583435, 304.5, 304.5416565, 304.5833435, 304.625, 304.6666565,
304.7083435, 304.75, 304.7916565, 304.8333435, 304.875, 304.9166565,
304.9583435), id = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
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0.093, 0.065, 0.038, 0.01, -0.02, -0.042, -0.06, -0.065, -0.065,
-0.05, -0.032, -0.006, 0.018, 0.046, 0.08, 0.116, 0.15, 0.186,
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0.079, 0.049, 0.026, 0.005, -0.01, -0.024, -0.023, -0.008, 0.006,
0.025, 0.052, 0.083, 0.117, 0.153, 0.189)), .Names = c("Date",
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我用来绘制图表的代码如下：
ggplot(jd1, aes(x=Date, y=value, colour =variable,linetype=variable))+geom_line()+facet_wrap(~id, ncol=1)
输出如下：
我只关心低潮和低点。我想找到建模和观察的点，然后用 1:1 线创建回归图。查看潮汐的下半部分甚至四分之一会有所帮助。谢谢你的帮助。