R: Können nicht angemessene Schätzungen von Optim erhalten()

Question

Hier sind meine Daten:

test <- structure(list(date = structure(c(16436, 16437, 16438, 16439, 
16440, 16441, 16442, 16443, 16444, 16445, 16446, 16447, 16448, 
16449, 16450, 16451, 16452, 16453, 16454, 16455, 16456, 16457, 
16458, 16459, 16460, 16461, 16462, 16463, 16464, 16465, 16466, 
16467, 16468, 16469, 16470, 16471, 16472, 16473, 16474, 16475, 
16476, 16477, 16478, 16479, 16480, 16481, 16482, 16483, 16484, 
16485, 16486, 16487, 16488, 16489, 16490, 16491, 16492, 16493, 
16494, 16495, 16496, 16497, 16498, 16499, 16500, 16501, 16502, 
16503, 16504, 16505, 16506, 16507, 16508, 16509, 16510, 16511, 
16512, 16513, 16514, 16515, 16516, 16517, 16518, 16519, 16520, 
16521, 16522, 16523, 16524, 16525, 16526, 16527, 16528, 16529, 
16530, 16531, 16532, 16533, 16534, 16535, 16536, 16537, 16538, 
16539, 16540, 16541, 16542, 16543, 16544, 16545, 16546, 16547, 
16548, 16549, 16550, 16551, 16552, 16553, 16554, 16555, 16556, 
16557, 16558, 16559, 16560, 16561, 16562, 16563, 16564, 16565, 
16566, 16567, 16568, 16569, 16570, 16571, 16572, 16573, 16574, 
16575, 16576, 16577, 16578, 16579, 16580, 16581, 16582, 16583, 
16584, 16585, 16586, 16587, 16588, 16589, 16590, 16591, 16592, 
16593, 16594, 16595, 16596, 16597, 16598, 16599, 16600, 16601, 
16602, 16603, 16604, 16605, 16606, 16607, 16608, 16609, 16610, 
16611, 16612, 16613, 16614, 16615, 16616, 16617, 16618, 16619, 
16620, 16621, 16622, 16623, 16624, 16625, 16626, 16627, 16628, 
16629, 16630, 16631, 16632, 16633, 16634, 16635, 16636, 16637, 
16638, 16639, 16640, 16641, 16642, 16643, 16644, 16645, 16646, 
16647, 16648, 16649, 16650, 16651, 16652, 16653, 16654, 16655, 
16656, 16657, 16658, 16659, 16660, 16661, 16662, 16663, 16664, 
16665, 16666, 16667, 16668, 16669, 16670, 16671, 16672, 16673, 
16674, 16675, 16676, 16677, 16678, 16679, 16680, 16681, 16682, 
16683, 16684, 16685, 16686, 16687, 16688, 16689, 16690, 16691, 
16692, 16693, 16694, 16695, 16696, 16697, 16698, 16699, 16700, 
16701, 16702, 16703, 16704, 16705, 16706, 16707, 16708, 16709, 
16710, 16711, 16712, 16713, 16714, 16715, 16716, 16717, 16718, 
16719, 16720, 16721, 16722, 16723, 16724, 16725, 16726, 16727, 
16728, 16729, 16730, 16731, 16732, 16733, 16734, 16735, 16736, 
16737, 16738, 16739, 16740, 16741, 16742, 16743, 16744, 16745, 
16746, 16747, 16748, 16749, 16750, 16751, 16752, 16753, 16754, 
16755, 16756, 16757, 16758, 16759, 16760, 16761, 16762, 16763, 
16764, 16765, 16766, 16767, 16768, 16769, 16770, 16771, 16772, 
16773, 16774, 16775, 16776, 16777, 16778, 16779, 16780, 16781, 
16782, 16783, 16784, 16785, 16786, 16787, 16788, 16789, 16790, 
16791, 16792, 16793, 16794, 16795, 16796, 16797, 16798, 16799, 
16800), class = "Date"), radn = c(9.66, 9.54, 8.21, 5, 5.98, 
9.39, 8.54, 9.68, 6.74, 2.95, 9.24, 7.39, 10.47, 9.04, 7.1, 4.12, 
6.42, 6.89, 10.96, 9.49, 11.72, 8.83, 11.48, 11.42, 11.49, 10.98, 
2.87, 11.92, 8.92, 4, 12.92, 8.37, 5.73, 4.47, 8.73, 5.76, 9.34, 
10.41, 6.72, 8.44, 13.34, 11.95, 12.2, 10.94, 10.5, 15.72, 14.63, 
15.67, 15.91, 14.79, 14.11, 15.89, 17.07, 17.62, 17.22, 14.93, 
11.17, 4.83, 8.78, 17.46, 10.35, 19.09, 19.39, 19.48, 19.12, 
18.94, 19.93, 20.24, 17.47, 6.07, 19.4, 18.26, 10, 6.33, 10.67, 
15.2, 21.39, 22.43, 18.02, 19.4, 18.55, 14.91, 9.15, 21.84, 22.8, 
23.16, 23.43, 24.16, 22.56, 23.58, 23.45, 25.09, 25.46, 22.85, 
17.05, 23.87, 12.45, 8.88, 25.7, 25.86, 17.28, 24.77, 25.08, 
15.62, 27.4, 27.35, 27.71, 26.91, 27.93, 27.99, 26.42, 20.49, 
27.9, 11.89, 10.38, 28.43, 28.74, 29.2, 27.62, 28.88, 28.81, 
28.92, 29.07, 24.41, 29.1, 26.43, 18, 23.94, 30.68, 29.47, 18.88, 
18.58, 25.79, 18.76, 12.18, 12.92, 20.18, 10.75, 14.09, 19.86, 
19.47, 15.9, 12.82, 22.62, 21.23, 24.62, 29.5, 30.21, 30.12, 
21.87, 25.45, 31.68, 32.18, 29.67, 17.27, 22.41, 24.28, 31.27, 
30, 30.12, 21.6, 32.76, 32.27, 32.24, 32.81, 32.45, 32.66, 30.52, 
30.5, 32.68, 32.85, 30.42, 32.62, 32.45, 31.29, 32.15, 25.84, 
26.21, 27.22, 26.36, 30.72, 26.26, 24.34, 21.45, 18.58, 25.95, 
29.09, 21.53, 21.88, 20.76, 17.56, 24.69, 22.83, 27.72, 28.07, 
31.18, 30.23, 28.86, 30.61, 30.79, 30.08, 27.28, 16.81, 23.82, 
30.09, 30.29, 30.45, 30.8, 31.12, 30.89, 30.19, 25.01, 24.27, 
18.93, 28.27, 26.62, 27.97, 22.9, 11.1, 22.29, 24.4, 27.78, 28.17, 
28.41, 26.01, 27.18, 25.08, 26.65, 27.95, 27.67, 24.39, 26.59, 
26.9, 26.54, 26.02, 25.31, 26.03, 22.22, 24.29, 21.01, 19.73, 
23.03, 25.38, 24.98, 24.74, 19.75, 20.24, 24.99, 21.01, 24.53, 
24.3, 23.95, 23.36, 22.92, 20.66, 15.42, 6.66, 15.28, 16.1, 16.73, 
22.14, 22.02, 21.59, 21.4, 21.41, 21.45, 15.48, 17.78, 19.93, 
15.58, 19.22, 17.29, 8.64, 8.94, 15.46, 12.52, 17.79, 18.36, 
18.28, 15.27, 13.04, 13.78, 17.88, 17.88, 17.5, 17.31, 16.84, 
14.55, 15.17, 7.43, 4.34, 5.23, 12.79, 15.84, 13.32, 15.43, 11.48, 
6.13, 14.64, 9.04, 5.09, 11.84, 9.86, 11.4, 4.92, 2.81, 5.76, 
7.92, 9.15, 13.14, 13.14, 9.94, 9.77, 11.15, 12.45, 12.33, 11.99, 
11.8, 6.92, 11.23, 6.2, 9.6, 4.89, 11.43, 11.05, 10.83, 7.44, 
5.4, 6.17, 3.52, 10.71, 10.64, 10.67, 10.6, 10.17, 6.02, 6.96, 
6.5, 7.43, 3.49, 2.03, 5.22, 5.02, 4.24, 4.44, 5.52, 2.72, 3.75, 
2.31, 8.38, 1.88, 3.07, 2.02, 2.66, 1.67, 5.77, 7.59, 1.9, 1.5, 
9.72, 2.66, 2.39, 1.67, 2.38, 9.88), maxt = c(-4.4, -1.9, 0.8, 
4.8, 6.8, 11, 13, 12.6, 11.4, 7, 5.8, 10, 7.2, 6.5, 5.9, 5.5, 
10.4, 12, 15.6, 11.2, 7.1, 6.3, 6.5, 9.4, 12.8, 14.6, 14.3, 7.8, 
11.9, 9.6, 4.5, 10.8, 13.2, 11.4, 14, 14.8, 14.9, 16.3, 17.2, 
15.4, 13.3, 12.4, 15.1, 17.6, 19.6, 19.8, 15.1, 12.8, 15.9, 18.7, 
18, 13.1, 10.6, 6, 7.6, 12.7, 14, 9.2, 8.3, 7.1, 9.5, 10, 6, 
10.1, 15.5, 18.4, 19.9, 19.6, 19.9, 21.5, 13.9, 17, 20.5, 20.6, 
22.7, 18.4, 18.5, 16, 19.9, 22.2, 19.1, 19.3, 12.6, 11.7, 17.1, 
22.2, 26.5, 19.7, 22.9, 26.3, 20.7, 12.2, 12.4, 16.3, 17.4, 12.7, 
12.7, 13, 11.4, 16.4, 20.6, 16.6, 18.4, 24.4, 11.7, 11.8, 18.6, 
23, 21.9, 23.3, 24.6, 26, 22.5, 21.6, 13.2, 11.9, 14.8, 21.2, 
25.8, 25.5, 22.6, 26.7, 27.6, 26.9, 27.2, 24.2, 18.6, 14.1, 20.5, 
21.6, 24.2, 22.6, 20.9, 19.6, 16.9, 14.8, 17.1, 20.6, 18.3, 16.9, 
20.2, 21.2, 19.6, 19.2, 22.6, 24, 23.9, 25.6, 27.1, 29.3, 30.2, 
31.6, 26.4, 24.7, 25.2, 21, 25.9, 26.4, 30.7, 33.4, 34.7, 29, 
30.5, 32.3, 31.9, 32.6, 32.6, 32.7, 33.6, 34, 31.6, 32.4, 31.4, 
31.5, 33.7, 35.9, 37.1, 38.8, 39.2, 38.9, 37.8, 38.4, 38.3, 38.6, 
37.2, 35.7, 27.9, 33.4, 32.7, 27.5, 29.2, 26.3, 26.9, 28, 29.1, 
31.1, 32, 33.1, 29.4, 29.2, 32.3, 34, 33, 29, 29.3, 30.8, 31.5, 
30.4, 24.9, 28.5, 33.6, 36.3, 37.7, 38.2, 34.5, 33.2, 33.9, 29.2, 
32.3, 25.4, 28.8, 32.4, 32.9, 34.9, 34.6, 36.2, 34.5, 32, 34.1, 
33.7, 33.3, 34.8, 34.5, 32.7, 32.3, 35.7, 35.3, 35, 34.2, 33.5, 
33.9, 31.4, 27.6, 30.9, 32.2, 30.5, 25.9, 23.5, 19.6, 24.1, 28.1, 
30.8, 33.2, 34.8, 35.8, 35.4, 33.5, 27.7, 21.7, 19.4, 20.1, 23.7, 
28.5, 31.5, 31.6, 31, 29.3, 31.2, 32.6, 30.5, 28.6, 29.8, 30.9, 
26.8, 21.1, 21.8, 20.4, 22.5, 24.9, 26.7, 27.1, 28, 30.7, 29.6, 
25.5, 29.3, 30.4, 30.8, 30.5, 29, 22, 18, 13.1, 16, 19, 19.1, 
19.3, 20.1, 20, 20.4, 18.6, 15.2, 13.7, 17.1, 22.3, 18.1, 6.3, 
6, 5.7, 7.1, 10.3, 11.1, 14.2, 8, 7.1, 8.9, 10.7, 12.3, 14.8, 
10.8, 3.2, 7.6, 12.6, 14.4, 9.6, 10.6, 11.7, 12.3, 13.4, 1.3, 
-0.9, -0.2, 0.6, 2.5, 4, 5.4, 7.3, 13, 8, 6.7, 11.5, 13.2, 14.2, 
14.9, 12.3, 5.5, 6.1, 11.1, 0.3, 0.5, 2, 2.8, 7, 4.9, 2.4, 7.3, 
6.2, 2.9, 0.5, -1.2, -2.5, -4, -2.7, -1.1, -3), mint = c(-15.9, 
-16.5, -14.4, -11.2, -5.7, -2.4, -2.5, -3.2, -4.3, -4.6, -1.5, 
-1, -0.9, -6.3, -7, -5.7, -1.2, -0.9, 0.3, -2.7, -5.9, -10.1, 
-8.7, -7.3, -5.7, -3.5, -1.2, -0.4, -0.9, -0.7, -4.3, -4.3, -2.8, 
1, 2.7, 3.1, 5.8, 6.2, 3.8, 2.2, -0.7, -1.5, -0.9, -0.3, 1, 1, 
-1.6, -3.8, -3.9, -1.9, -0.6, -0.8, -3.8, -7, -8.8, -7, -2.2, 
-0.3, -1.1, -2.9, -5.1, -5.2, -9.2, -9.7, -6.9, -4.2, -3.1, -3.5, 
-3.8, -2.3, 3.5, 0.3, 0.7, 5.8, 7, 7.4, 2.3, -0.6, -2.2, 0.7, 
0.9, 1.6, 3.8, -0.9, -2.5, 1, 2.6, 1.8, -1.6, 2.3, -4.2, -6.6, 
-4.7, -4.2, -0.5, -1.4, -3, 0.3, -2.9, -2.3, 1.1, -0.4, -1.5, 
0.5, -6.1, -7.3, -5, -0.5, 0.6, 0.7, 1.2, 2.9, 4.3, 4.7, 2.1, 
0.3, 0.5, 1.4, 3.4, 5, 4.9, 4.2, 6.3, 6.7, 6, 6.3, 3.6, 3.5, 
3.7, 1.1, 1.9, 4.9, 0.7, 1.2, 5.8, 5.6, 4, 6.2, 8.3, 7, 6, 4.7, 
7, 9.2, 8.1, 6.9, 7.9, 8.6, 9.6, 9.4, 10.3, 10.4, 9.6, 8.2, 9.4, 
9.8, 7.2, 9.4, 10.8, 12.4, 14.5, 11.8, 11, 10.7, 11.3, 10.8, 
9.7, 10.4, 10.6, 12.1, 10.3, 10.5, 11.3, 10, 12.6, 13.6, 17.4, 
19.9, 19.9, 18.9, 18.4, 18.9, 20.1, 19, 17, 16.9, 14.8, 13.1, 
14, 11.5, 10.6, 11.1, 12.7, 11.4, 11.9, 12.5, 13.3, 13.6, 13.2, 
11.8, 11.8, 12.6, 15, 11.4, 10, 9.6, 9.3, 9.3, 8.2, 9.6, 9.7, 
12, 14.3, 16.1, 16.5, 12.8, 13.7, 11.3, 10.3, 12.2, 11.4, 11.8, 
11.1, 10.9, 11.2, 13, 11.8, 9, 9.7, 8.9, 10.1, 10, 11.5, 10.6, 
12.2, 10.9, 12.6, 11.9, 11.9, 13.1, 13.4, 11.4, 6.9, 6, 7.7, 
9.7, 7.8, 2.2, 1.5, 0.9, 2.3, 4.8, 6.3, 8.3, 10.4, 11.2, 12.8, 
11, 7.5, 6.1, 5.5, 2.4, 3.5, 5.8, 5.9, 6.2, 5.6, 6.1, 7.4, 9.9, 
7.8, 6.4, 7.8, 11, 10.1, 4.8, 3.5, 6.6, 4.6, 5.5, 5.9, 9.8, 8.3, 
8.6, 6.4, 4.4, 6, 7.1, 6.9, 7.5, 7.8, 6.9, 3.9, 1.8, 0.3, 0.3, 
-0.5, 3.2, 2.4, -0.3, 0.2, 5.1, -1.5, -1.4, 4.7, 5.6, 1.6, -1.3, 
-3.8, -4.1, -4.6, -3.5, -0.8, -1.4, -6.5, -6, -5, -4.9, -3.9, 
-4.2, -6.1, -1.7, -0.2, -0.3, -3.6, -7.1, -6.4, -3.4, -5.2, -8.6, 
-9.6, -13.8, -16.3, -15.6, -14.5, -11.8, -4.6, 0, -7.6, -7.7, 
-1.3, 4.8, 4.6, 2.3, 0.1, -2.2, -1.4, -2.6, -4.7, -9, -6.8, -4.4, 
-3.7, -3.9, -5.1, 0, -1.8, -3.2, -9, -14.2, -17.4, -13, -8.2, 
-12.7, -17.5), rain = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.8, 
0.96, 0, 0, 0, 1.38, 0.25, 0.32, 0, 0, 0, 0, 0, 0, 0, 0, 5.68, 
0, 0, 0, 0, 0, 1.12, 0, 0, 0, 4.24, 0.13, 6.84, 1.44, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.28, 2.13, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.65, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.65, 0, 3.6, 1.9, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.59, 1.19, 11.03, 5.43, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.77, 0, 0, 0, 0, 0, 5.06, 5.6, 
0.01, 2.23, 5.45, 7.43, 4.47, 0.11, 4.02, 6.36, 0.38, 0.79, 1.46, 
0, 0, 0, 0, 0, 0, 0, 0, 0.82, 3.06, 0.06, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.37, 0, 
2.3, 1.74, 3.2, 1.72, 3.53, 2, 1.08, 0.46, 0.38, 0.3, 0, 0, 0, 
0.47, 0, 0, 0.56, 4.86, 9.66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.86, 
0, 0, 0, 0, 2.44, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0.55, 0.83, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16.08, 
0.93, 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.24, 4.25, 14.52, 
13.45, 0, 0, 0, 0, 0, 0, 0, 0, 1.2, 1.23, 0, 0, 4.15, 11.05, 
2.29, 0, 0, 0, 0, 0.77, 3.04, 0, 0, 0, 0, 0, 0.88, 0, 0, 0, 0, 
0, 0, 0, 0, 0.94, 0, 0, 0, 0, 0, 0, 0.02, 0, 0, 0, 0, 0, 0, 0, 
0.66, 1.85, 0.95, 0.61, 3.89, 0, 0, 1.23, 4.81, 0, 1.96, 1.67, 
6.94, 9.65, 0, 1.99, 0, 0, 2.24, 2.67, 0.16, 0.52), evap = c(8.48, 
8.48, 8.48, 8.48, 8.48, 8.48, 8.48, 8.31, 8.31, 8.31, 8.31, 8.31, 
8.31, 8.31, 8.09, 8.09, 8.09, 8.09, 8.09, 8.09, 8.09, 7.86, 7.86, 
7.86, 7.86, 7.86, 7.86, 7.86, 7.62, 7.62, 7.62, 7.62, 7.62, 7.62, 
7.62, 7.39, 7.39, 7.39, 7.39, 7.39, 7.39, 7.39, 7.16, 7.16, 7.16, 
7.16, 7.16, 7.16, 7.16, 6.93, 6.93, 6.93, 6.93, 6.93, 6.93, 6.93, 
6.71, 6.71, 6.71, 6.71, 6.71, 6.71, 6.71, 6.48, 6.48, 6.48, 6.48, 
6.48, 6.48, 6.48, 6.23, 6.23, 6.23, 6.23, 6.23, 6.23, 6.23, 5.96, 
5.96, 5.96, 5.96, 5.96, 5.96, 5.96, 5.66, 5.66, 5.66, 5.66, 5.66, 
5.66, 5.66, 5.32, 5.32, 5.32, 5.32, 5.32, 5.32, 5.32, 4.95, 4.95, 
4.95, 4.95, 4.95, 4.95, 4.95, 4.56, 4.56, 4.56, 4.56, 4.56, 4.56, 
4.56, 4.15, 4.15, 4.15, 4.15, 4.15, 4.15, 4.15, 3.75, 3.75, 3.75, 
3.75, 3.75, 3.75, 3.75, 3.38, 3.38, 3.38, 3.38, 3.38, 3.38, 3.38, 
3.05, 3.05, 3.05, 3.05, 3.05, 3.05, 3.05, 2.78, 2.78, 2.78, 2.78, 
2.78, 2.78, 2.78, 2.58, 2.58, 2.58, 2.58, 2.58, 2.58, 2.58, 2.45, 
2.45, 2.45, 2.45, 2.45, 2.45, 2.45, 2.37, 2.37, 2.37, 2.37, 2.37, 
2.37, 2.37, 2.35, 2.35, 2.35, 2.35, 2.35, 2.35, 2.35, 2.38, 2.38, 
2.38, 2.38, 2.38, 2.38, 2.38, 2.46, 2.46, 2.46, 2.46, 2.46, 2.46, 
2.46, 2.57, 2.57, 2.57, 2.57, 2.57, 2.57, 2.57, 2.72, 2.72, 2.72, 
2.72, 2.72, 2.72, 2.72, 2.9, 2.9, 2.9, 2.9, 2.9, 2.9, 2.9, 3.1, 
3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.33, 3.33, 3.33, 3.33, 3.33, 3.33, 
3.33, 3.57, 3.57, 3.57, 3.57, 3.57, 3.57, 3.57, 3.83, 3.83, 3.83, 
3.83, 3.83, 3.83, 3.83, 4.13, 4.13, 4.13, 4.13, 4.13, 4.13, 4.13, 
4.47, 4.47, 4.47, 4.47, 4.47, 4.47, 4.47, 4.85, 4.85, 4.85, 4.85, 
4.85, 4.85, 4.85, 5.26, 5.26, 5.26, 5.26, 5.26, 5.26, 5.26, 5.67, 
5.67, 5.67, 5.67, 5.67, 5.67, 5.67, 6.08, 6.08, 6.08, 6.08, 6.08, 
6.08, 6.08, 6.46, 6.46, 6.46, 6.46, 6.46, 6.46, 6.46, 6.79, 6.79, 
6.79, 6.79, 6.79, 6.79, 6.79, 7.09, 7.09, 7.09, 7.09, 7.09, 7.09, 
7.09, 7.35, 7.35, 7.35, 7.35, 7.35, 7.35, 7.35, 7.6, 7.6, 7.6, 
7.6, 7.6, 7.6, 7.6, 7.84, 7.84, 7.84, 7.84, 7.84, 7.84, 7.84, 
8.07, 8.07, 8.07, 8.07, 8.07, 8.07, 8.07, 8.28, 8.28, 8.28, 8.28, 
8.28, 8.28, 8.28, 8.46, 8.46, 8.46, 8.46, 8.46, 8.46, 8.46, 8.58, 
8.58, 8.58, 8.58, 8.58, 8.58, 8.58, 8.63, 8.63, 8.63, 8.63, 8.63, 
8.63, 8.63, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6), index = 8767:9131), .Names = c("date", 
"radn", "maxt", "mint", "rain", "evap", "index"), na.action = structure(1L, .Names = "1", class = "omit"), row.names = 8768:9132, class = "data.frame") 

ich eine Funktion, um es zu optimieren versuchen, einige Daten zu simulieren. Ich habe dies in der Vergangenheit mit anderen Datensätzen mit Erfolg gemacht, aber mit diesen Daten konvergiert optim aber optisch ist die Passform furchtbar. Ich mache einen viel besseren Job mit Raten und Überprüfen. Hier schaue ich auf minimale Temperatur. Ich habe viele Jahre Daten, aber im Interesse des Weltraums habe ich nur 1 Jahr eingeschlossen.

Hier ist meine Optimierung Code:

TMIN <- function(a,b,x){a*sin(b*x)} 

plot(h$mint~h$index,type='l') 
curve(TMIN(x, a=20, b=.017),add=TRUE, col="red") 

normTMIN<-function(params,k){ 
    a=params[1] 
    b=params[2] 
    c=params[3] 
    Mean<-mean(a*sin(b*k)) 
    -sum(dnorm(k,mean=Mean,sd=c,log=TRUE)) #shape= Mean(a,b)/scale 
} 

optTMIN <- optim(par=c(a=60,b=.017,c=1),k=test$mint,fn=normTMIN) #par doesn't equal params 
optTMIN 

curve(TMIN(optTMIN$par[1],optTMIN$par[2],x), add=TRUE,col="blue") 

Ich kann nicht herausfinden, warum optim ist so schrecklich schief gehen. Danke im Voraus.

Answer 1

Haben Sie so etwas wie die folgenden (finden Liste Quadratschätzung) tun:

head(test) 
TMIN <- function(a,b,x){a*sin(b*x)} 

plot(test$mint~test$index,type='l') 
curve(TMIN(x, a=20, b=.017),add=TRUE, col="red") 

normTMIN<-function(params,k,x){ 
    a=params[1] 
    b=params[2] 
    sum((k - TMIN(a,b,x))^2) 
} 

optTMIN <- optim(par=c(a=1,b=0.001),k=test$mint,x=test$index,fn=normTMIN, control=list(trace = TRUE)) #par doesn't equal params 
optTMIN 

curve(TMIN(optTMIN$par[1],optTMIN$par[2],x), add=TRUE,col="blue") 

#$par 
#   a   b 
#10.97271664 0.01349994