phenoPhase(wq)
phenoPhase()所属R语言包：wq
Phenological phase
物候期
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Finds various measures of the phase of the annual cycle, or of some specified month range.
查找的年度周期的阶段，或的一些指定月份范围内的各种措施。
用法----------Usage----------
## S4 method for signature 'ts'
phenoPhase(x, mon.range = c(1, 12), ...)
## S4 method for signature 'zoo'
phenoPhase(x, mon.range = c(1, 12), out = c('date', 'doy', 'julian'), ...)
参数----------Arguments----------
参数：x
A monthly time series, or a class "zoo" object.
一个月度时间序列，或一类"zoo"对象的。
参数：mon.range
A vector of two numbers specifying the month range to be considered.
两个数字指定月份范围的向量加以考虑。
参数：out
The form of the output.
的形式输出。
参数：...
Additional arguments to be passed for changing integration defaults.
其他参数可以通过改变集成默认。
Details
详细信息----------Details----------
phenoPhase gives three measures of the phasing of a seasonal cycle: the time of the maximum (Cloern and Jassby 2008), the fulcrum or center of gravity, and the weighted mean month (Colebrook 1979). The latter has sometimes been referred to in the literature as “centre of gravity”, but it is not actually the same. These measures differ in their sensitivity to changes in the seasonal pattern, and therefore also in their susceptibility to sampling variability. The time of maximum is the most sensitive, the weighted mean the least.
phenoPhase提出了三项措施逐步的季节性周期：时间的最大（2008年Cloern和Jassby），支点或重心，加权平均月（科尔布鲁克1979年）。后者有时被称为在文献中的“重心”，但它实际上是不一样的。这些措施的敏感性不同，在季节性的图案的变化，也因此在其易感性抽样可变性。最大的时间是最敏感的，加权平均最少的。
These measures can be restricted to a subset of the year by giving the desired range of month numbers. This can be useful for isolating measures of, say, the spring and autumn phytoplankton blooms in temperate waters. In the case of a monthly time series, a non-missing value is required for every month or the result will be NA, so using a period shorter than one year can also help avoid any months that are typically not covered by the sampling program. Similarly, in the case of dated observations, a shorter period can help avoid times of sparse data.
这些措施，可以被限制为一个子集的年给予所需的范围内的月份数。这可能是有用的，也就是说，在温带水域春季和秋季浮游植物大量繁殖隔离措施。非缺失值的月度时间序列的情况下，每个月需要的结果将是NA，使用期限短于一年，还可以帮助避免任何个月，通常不包括在抽样方案。同样的，过时的观察的情况下，更短的时间内可以帮助避免稀疏数据的时候。
The measures are annum-centric, i.e., they reflect the use of calendar year as the annum, which may not be appropriate for cases in which important features occur in winter and span two calendar years. Such cases can be handled by lagging the time series by an appropriate number of months, or by subtracting an appropriate number of days from the individual dates.
这些措施是每年为中心的，也就是说，它们反映为公历年度每年的使用可能不适合的情况下，其中重要的功能发生在冬季，跨越两个日历年。这种情况下，可以通过以下来处理滞后的时间系列由一个相应的月数，或通过从个别日期中减去相应的天数。
tsMake can be used to produce "ts" and "zoo" objects suitable as arguments to this function.
tsMake可以用于生产"ts"和"zoo"对象适合作为这个函数的参数。
The default parameters used for the integrate function in phenoPhase may fail for certain datasets. Try increasing the number of subdivisions above its default of 100 by adding, for example, subdivisions = 1000 to the arguments of phenoPhase.
默认的参数用于integratephenoPhase功能的可能会失败某些数据集。尝试增加其默认值为100以上的细分数的增加，例如，subdivisions = 1000的参数phenoPhase。
值----------Value----------
A data frame. In the case of monthly time series, the results are all given as decimal months of the year. In the case of dated observations, the results can be dates, day of the year, or julian day with an origin of 1970-01-01, depending on the option out.
一个数据框。在每月的时间序列的情况下，结果都为十进制的一年中的月份。过时的观察的情况下，其结果可能是起源1970-01-01日期，一天的一年，或儒略日，根据选项“out。
参考文献----------References----------
参见----------See Also----------
phenoAmp, tsMake
phenoAmp，tsMake
实例----------Examples----------
# ts example[TS例子]
y <- sfbayChla[, 's27']
p1 <- phenoPhase(y)
p1
apply(p1, 2, sd, na.rm=TRUE) # max.mon > fulcrum > mean.wt [max.mon支点> mean.wt]
phenoPhase(y, c(3, 10))
# zoo example[动物园例如]
sfb <- wqData(sfbay, c(1,3,4), 5:12, site.order = TRUE, type = "wide",
time.format = "%m/%d/%Y")
y <- tsMake(sfb, focus = 'chl', layer = c(0, 5), type = 'zoo')
phenoPhase(y[, 's27'])
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 23:07:05
