我想计算此时间序列中出现峰值的月份,并确定这些变化是否超过分析记录。我能从这个阶段获得这些信息吗?我怎么能在R?
中做到这一点这是时间序列
[1] -2.566983e-02 -5.782524e-02 -7.808027e-02 -7.600751e-02 -5.500182e-02 -1.794568e-02 2.287965e-02 6.176569e-02 8.517858e-02 8.618686e-02 6.599044e-02 2.595632e-02
[13] -2.468891e-02 -7.291849e-02 -1.013152e-01 -1.052718e-01 -7.944368e-02 -2.482406e-02 3.896659e-02 9.315530e-02 1.286337e-01 1.274909e-01 9.111597e-02 2.842469e-02
[25] -4.845922e-02 -1.157328e-01 -1.537427e-01 -1.534016e-01 -1.060450e-01 -2.458452e-02 6.501879e-02 1.385970e-01 1.746728e-01 1.629937e-01 1.037831e-01 1.111534e-02
[37] -8.784113e-02 -1.601244e-01 -1.872461e-01 -1.614843e-01 -9.001538e-02 8.044579e-03 1.037991e-01 1.691924e-01 1.878601e-01 1.587651e-01 8.405491e-02 -1.356792e-02
[49] -1.069555e-01 -1.710607e-01 -1.853867e-01 -1.499666e-01 -7.398990e-02 1.654048e-02 1.006945e-01 1.533522e-01 1.701250e-01 1.431100e-01 8.169068e-02 2.343733e-05
[61] -8.011875e-02 -1.382533e-01 -1.624560e-01 -1.458858e-01 -9.018088e-02 -1.271360e-02 6.579380e-02 1.277067e-01 1.637702e-01 1.500510e-01 1.026965e-01 2.813767e-02
[73] -5.578174e-02 -1.241554e-01 -1.614667e-01 -1.555724e-01 -1.118590e-01 -4.256574e-02 3.614970e-02 1.097938e-01 1.532000e-01 1.612439e-01 1.229504e-01 4.904072e-02
[85] -3.726522e-02 -1.116908e-01 -1.535943e-01 -1.555642e-01 -1.110113e-01 -3.607084e-02 4.671452e-02 1.141403e-01 1.515199e-01 1.411410e-01 9.221573e-02 1.711825e-02
[97] -6.117735e-02 -1.198699e-01 -1.431554e-01 -1.232685e-01 -6.267357e-02 1.360005e-02 8.311781e-02 1.294568e-01 1.384708e-01 1.110949e-01 4.826190e-02 -3.187023e-02
[109] -1.029242e-01 -1.465521e-01 -1.493273e-01 -1.069210e-01 -3.451630e-02 4.808568e-02 1.152376e-01 1.475487e-01 1.423903e-01 9.678471e-02 2.042843e-02 -6.301876e-02
[121] -1.307709e-01 -1.621329e-01 -1.482143e-01 -9.408793e-02 -1.091879e-02 7.770917e-02 1.466600e-01 1.752333e-01 1.613551e-01 1.014390e-01 1.233963e-02 -8.395569e-02
[133] -1.568942e-01 -1.900819e-01 -1.721025e-01 -1.060657e-01 -9.791183e-03 8.962102e-02 1.643729e-01 1.959725e-01 1.698956e-01 9.874419e-02 4.063712e-03 -9.332515e-02
[145] -1.653777e-01 -1.908999e-01 -1.714995e-01 -1.056551e-01 -9.412571e-03 9.176901e-02 1.704038e-01 2.107884e-01 1.959427e-01 1.302384e-01 2.709246e-02 -8.280759e-02
[157] -1.722022e-01 -2.242869e-01 -2.189376e-01 -1.606955e-01 -5.842590e-02 5.697796e-02 1.590890e-01 2.238129e-01 2.332621e-01 1.821653e-01 8.796006e-02 -2.804040e-02
[169] -1.370321e-01 -2.171222e-01 -2.378465e-01 -2.004218e-01 -1.160496e-01 -4.281969e-03 1.050972e-01 1.908922e-01 2.247106e-01 2.014388e-01 1.247218e-01 2.324572e-02
[181] -7.522908e-02 -1.497589e-01 -1.809624e-01 -1.666022e-01 -1.176099e-01 -4.498645e-02 3.233885e-02 9.812366e-02 1.361637e-01 1.352237e-01 1.010775e-01 4.642129e-02
[193] -1.229179e-02 -6.198903e-02 -8.762626e-02 -8.745873e-02 -7.072290e-02 -4.123783e-02 -8.680191e-03 1.983371e-02 4.176359e-02 4.857435e-02 4.229918e-02 2.785419e-02
[205] 1.123948e-02 -7.127771e-03 -2.058425e-02 -2.566657e-02 -2.470011e-02 -1.869947e-02 -1.005953e-02 4.231329e-03 2.079108e-02 3.393548e-02 3.458949e-02 2.465338e-02
[217] 8.125533e-03 -9.914837e-03 -2.958697e-02 -3.901624e-02 -4.084610e-02 -2.888188e-02 -1.052842e-02 1.739696e-02 3.451113e-02 4.782416e-02 5.209275e-02 4.578052e-02
[229] 2.652363e-02 1.504811e-04 -2.352872e-02 -4.675681e-02 -5.486831e-02 -5.110543e-02 -3.164919e-02 -2.465634e-03 3.044004e-02 5.946521e-02 7.533064e-02 6.878881e-02
[241] 3.968605e-02 -8.599631e-04 -3.705050e-02 -6.874023e-02 -7.858607e-02 -6.366839e-02 -2.886664e-02 1.470032e-02 5.256284e-02 7.871812e-02 7.941835e-02 5.261808e-02
[253] 3.232945e-03 -4.866670e-02 -8.060033e-02 -8.655462e-02 -6.345511e-02 -1.341964e-02 4.022795e-02 7.877580e-02 9.041708e-02 7.017194e-02 2.731874e-02 -2.426977e-02
[265] -6.618300e-02 -8.652564e-02 -7.566890e-02 -4.360560e-02 2.427347e-04 4.560736e-02 7.147917e-02 7.334999e-02 5.439404e-02 1.828790e-02 -2.180237e-02 -5.176644e-02
[277] -6.194357e-02 -5.263502e-02 -2.702600e-02 5.459462e-03 2.764591e-02 3.515949e-02 2.904689e-02 9.856334e-03 -1.099115e-02 -2.476568e-02 -2.473909e-02 -1.470535e-02
[289] 9.901777e-04 1.269958e-02 1.628164e-02 1.215371e-02 -7.787407e-05 -1.170293e-02 -2.252639e-02 -2.297631e-02 -1.216422e-02 7.715951e-03 2.662490e-02 3.497172e-02
[301] 2.913067e-02 1.052321e-02 -1.770285e-02 -4.316586e-02 -5.294941e-02 -4.598436e-02 -2.154287e-02 1.347715e-02 4.857204e-02 6.759757e-02 6.256019e-02 3.480956e-02
[313] -8.177469e-03 -4.727875e-02 -7.296587e-02 -7.333275e-02 -4.710260e-02 -2.676638e-03 4.868405e-02 8.367411e-02 9.452564e-02 7.463526e-02 2.867804e-02 -2.773269e-02
[325] -7.303544e-02 -9.532996e-02 -8.841880e-02 -5.778710e-02 -9.568579e-03 4.231762e-02 7.537721e-02 8.680084e-02 7.547977e-02 4.510019e-02 3.801842e-03 -3.529420e-02
[337] -6.033518e-02 -6.668869e-02 -5.458891e-02 -2.999038e-02 -2.593124e-04 2.806880e-02 4.193105e-02 4.383955e-02 3.707603e-02 2.022521e-02 6.101334e-03 -5.717493e-03
[349] -1.234244e-02 -1.620367e-02 -1.806666e-02 -1.922020e-02 -2.110791e-02 -2.127266e-02 -2.096110e-02 -1.714399e-02 -2.783072e-03 1.654030e-02 3.282535e-02 4.414188e-02
[361] 4.770084e-02 3.847246e-02 1.832072e-02 -1.056649e-02 -3.722579e-02 -5.740149e-02 -6.341912e-02 -5.426390e-02 -2.980793e-02 7.470599e-04 3.212034e-02 5.011929e-02
[373] 5.734303e-02 4.622466e-02 2.630451e-02 1.905363e-03 -2.046357e-02 -3.383679e-02 -3.753406e-02 -2.872917e-02 -1.366504e-02 1.757055e-03 1.296441e-02 1.619348e-02
[385] 1.238192e-02 5.528508e-03 -5.078213e-03 -1.051610e-02 -1.070992e-02 -3.608823e-03 4.587764e-03 1.269367e-02 1.821489e-02 1.886193e-02 9.326559e-03 -6.350481e-03
[397] -2.268550e-02 -3.562078e-02 -3.750427e-02 -2.826171e-02 -9.722588e-03 1.425940e-02 3.382628e-02 4.683378e-02 4.966529e-02 3.399604e-02 7.296378e-03 -2.218337e-02
答案 0 :(得分:1)
尝试?which.max
> which.max( iris[,1] )
[1] 132
这将为您提供给定系列中最大值的索引。但是,您需要提供更多信息。这些数据是如何存储的,是月度数据吗? Please refer to this in the future.