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   {130.00,       -40.7839        }}

but have no idea how to do the trend-reduction between those data gaps (i.e., outside of the regions with data = 99999). The position of those regions is not constant. After the reduction is performed, the position of the "no data"-values should be the same as before

but have no idea how to do the trend-reduction between those data gaps (i.e., outside of the regions with data = 99999). The position of those regions is not constant. After the reduction is performed, the position of the "no data"-values should be the same as before. Due to answer 1, unfortunately there is no periodically or cyclically behaviour in the data at all. Here, for example, is another, but complete data set:

{{100.00, 0.303999 }, {100.05, 0.303999 }, {100.09, 0.176000 }, {100.15, 0.303999 }, {100.20, 0.176000 }, {100.25, 0.303999 }, {100.30, 0.431999 }, {100.34, 0.431999 }, {100.40, 0.559999 }, {100.45, 0.687999 }, {100.50, 0.687999 }, {100.55, 0.943999 }, {100.59, 1.07200 }, {100.65, 1.20000 }, {100.70, 1.32800 }, {100.75, 1.32800 }, {100.80, 1.20000 }, {100.84, 1.20000 }, {100.90, 1.20000 }, {100.95, 1.07200 }, {101.00, 1.07200 }, {101.05, 1.07200 }, {101.09, 1.07200 }, {101.15, 1.07200 }, {101.20, 1.07200 }, {101.25, 1.07200 }, {101.30, 0.943999 }, {101.34, 0.943999 }, {101.40, 0.943999 }, {101.45, 0.687999 }, {101.50, 0.431999 }, {101.55, 0.303999 }, {101.59, 4.800009E-002 }, {101.65, -8.000003E-002 }, {101.70, -0.207999 }, {101.75, -0.464000 }, {101.80, -0.719999 }, {101.84, -0.847999 }, {101.90, -0.847999 }, {101.95, -0.975999 }, {102.00, -1.10400 }, {102.05, -1.23200 }, {102.09, -1.36000 }, {102.15, -1.36000 }, {102.20, -1.36000 }, {102.25, -1.36000 }, {102.30, -1.36000 }, {102.34, -1.23200 }, {102.40, -1.10400 }, {102.45, -1.10400 }, {102.50, -0.975999 }, {102.55, -0.847999 }, {102.59, -0.719999 }, {102.65, -0.591999 }, {102.70, -0.464000 }, {102.75, -0.207999 }, {102.80, 4.800009E-002 }, {102.84, 4.800009E-002 }, {102.90, 0.431999 }, {102.95, 0.687999 }, {103.00, 0.943999 }, {103.05, 1.20000 }, {103.09, 1.32800 }, {103.15, 1.32800 }, {103.20, 1.58400 }, {103.25, 1.71200 }, {103.30, 1.84000 }, {103.34, 1.96800 }, {103.40, 2.09600 }, {103.45, 2.22400 }, {103.50, 2.22400 }, {103.55, 2.35199 }, {103.59, 2.35199 }, {103.65, 2.48000 }, {103.70, 2.48000 }, {103.75, 2.60800 }, {103.80, 2.86399 }, {103.84, 2.86399 }, {103.90, 2.86399 }, {103.95, 2.86399 }, {104.00, 2.99200 }, {104.05, 2.86399 }, {104.09, 2.73600 }, {104.15, 2.60800 }, {104.20, 2.60800 }, {104.25, 2.73600 }, {104.30, 2.48000 }, {104.34, 2.48000 }, {104.40, 2.48000 }, {104.45, 2.35199 }, {104.50, 2.22400 }, {104.55, 2.09600 }, {104.59, 1.96800 }, {104.65, 1.84000 }, {104.70, 1.84000 }, {104.75, 1.71200 }, {104.80, 1.58400 }, {104.84, 1.71200 }, {104.90, 1.45600 }, {104.95, 1.45600 }, {105.00, 1.32800 }, {105.05, 1.32800 }, {105.09, 1.07200 }, {105.15, 1.07200 }, {105.20, 0.943999 }, {105.25, 0.943999 }, {105.30, 0.943999 }, {105.34, 0.815999 }, {105.40, 0.559999 }, {105.45, 4.800009E-002 }, {105.50, -0.336000 }, {105.55, -0.975999 }, {105.59, -1.36000 }, {105.65, -2.00000 }, {105.70, -2.51200 }, {105.75, -2.89599 }, {105.80, -3.02400 }, {105.84, -3.02400 }, {105.90, -2.89599 }, {105.95, -2.12800 }, {106.00, -1.23200 }, {106.05, -0.464000 }, {106.09, -8.000003E-002 }, {106.15, 0.303999 }, {106.20, 0.559999 }, {106.25, 0.687999 }, {106.30, 0.943999 }, {106.34, 1.07200 }, {106.40, 1.32800 }, {106.45, 1.45600 }, {106.50, 1.58400 }, {106.55, 1.58400 }, {106.59, 1.58400 }, {106.65, 1.58400 }, {106.70, 1.58400 }, {106.75, 1.45600 }, {106.80, 1.32800 }, {106.84, 1.45600 }, {106.90, 1.32800 }, {106.95, 1.32800 }, {107.00, 1.32800 }, {107.05, 1.20000 }, {107.09, 1.07200 }, {107.15, 0.943999 }, {107.20, 0.943999 }, {107.25, 0.815999 }, {107.30, 0.815999 }, {107.34, 0.687999 }, {107.40, 0.559999 }, {107.45, 0.559999 }, {107.50, 0.559999 }, {107.55, 0.431999 }, {107.59, 0.431999 }, {107.65, 0.559999 }, {107.70, 0.431999 }, {107.75, 0.687999 }, {107.80, 0.815999 }, {107.84, 1.07200 }, {107.90, 1.07200 }, {107.95, 1.32800 }, {108.00, 1.45600 }, {108.05, 99999.0 }, {108.09, 99999.0 }, {108.15, 99999.0 }, {108.20, 99999.0 }, {108.25, 99999.0 }, {108.30, 99999.0 }, {108.34, 99999.0 }, {108.40, 99999.0 }, {108.45, 99999.0 }, {108.50, 99999.0 }, {108.55, 99999.0 }, {108.59, 99999.0 }, {108.65, 99999.0 }, {108.70, 99999.0 }, {108.75, 99999.0 }, {108.80, 99999.0 }, {108.84, 99999.0 }, {108.90, 99999.0 }, {108.95, 99999.0 }, {109.00, 99999.0 }, {109.05, 99999.0 }, {109.09, 99999.0 }, {109.15, 99999.0 }, {109.20, 99999.0 }, {109.25, 99999.0 }, {109.30, 99999.0 }, {109.34, 99999.0 }, {109.40, 99999.0 }, {109.45, 99999.0 }, {109.50, 99999.0 }, {109.55, 99999.0 }, {109.59, 99999.0 }, {109.65, 99999.0 }, {109.70, 99999.0 }, {109.75, 99999.0 }, {109.80, 99999.0 }, {109.84, 99999.0 }, {109.90, 99999.0 }, {109.95, 99999.0 }, {110.00, 99999.0 }, {110.05, 99999.0 }, {110.09, 99999.0 }, {110.15, 99999.0 }, {110.20, 99999.0 }, {110.25, 99999.0 }, {110.30, 99999.0 }, {110.34, 99999.0 }, {110.40, 99999.0 }, {110.45, 99999.0 }, {110.50, 99999.0 }, {110.55, 99999.0 }, {110.59, 99999.0 }, {110.65, 99999.0 }, {110.70, 99999.0 }, {110.75, 99999.0 }, {110.80, 99999.0 }, {110.84, 99999.0 }, {110.90, 99999.0 }, {110.95, 99999.0 }, {111.00, 99999.0 }, {111.05, 99999.0 }, {111.09, 99999.0 }, {111.15, 99999.0 }, {111.20, 99999.0 }, {111.25, 99999.0 }, {111.30, 99999.0 }, {111.34, 99999.0 }, {111.40, 99999.0 }, {111.45, 99999.0 }, {111.50, 99999.0 }, {111.55, 99999.0 }, {111.59, 99999.0 }, {111.65, 99999.0 }, {111.70, 99999.0 }, {111.75, 99999.0 }, {111.80, 99999.0 }, {111.84, 99999.0 }, {111.90, 99999.0 }, {111.95, 99999.0 }, {112.00, 4.800009E-002 }, {112.05, -8.000003E-002 }, {112.09, -8.000003E-002 }, {112.15, -8.000003E-002 }, {112.20, -8.000003E-002 }, {112.25, -8.000003E-002 }, {112.30, -0.336000 }, {112.34, -0.464000 }, {112.40, -0.336000 }, {112.45, -0.336000 }, {112.50, -0.336000 }, {112.55, -0.336000 }, {112.59, -0.336000 }, {112.65, -0.336000 }, {112.70, -8.000003E-002 }, {112.75, 4.800009E-002 }, {112.80, 0.176000 }, {112.84, 0.303999 }, {112.90, 0.559999 }, {112.95, 0.687999 }, {113.00, 0.943999 }, {113.05, 1.07200 }, {113.09, 1.20000 }, {113.15, 1.45600 }, {113.20, 1.71200 }, {113.25, 1.96800 }, {113.30, 2.35199 }, {113.34, 2.86399 }, {113.40, 3.12000 }, {113.45, 3.37599 }, {113.50, 3.63200 }, {113.55, 3.88799 }, {113.59, 3.88799 }, {113.65, 3.88799 }, {113.70, 4.01600 }, {113.75, 3.88799 }, {113.80, 4.01600 }, {113.84, 3.88799 }, {113.90, 3.75999 }, {113.95, 3.50400 }, {114.00, 2.99200 }, {114.05, 2.48000 }, {114.09, 1.96800 }, {114.15, 1.58400 }, {114.20, 0.943999 }, {114.25, 0.431999 }, {114.30, -0.336000 }, {114.34, -0.847999 }, {114.40, -1.23200 }, {114.45, -1.61600 }, {114.50, -2.00000 }, {114.55, -2.25599 }, {114.59, -2.38399 }, {114.65, -2.51200 }, {114.70, -2.64000 }, {114.75, -2.89599 }, {114.80, -3.02400 }, {114.84, -2.89599 }, {114.90, -2.76799 }, {114.95, -2.64000 }, {115.00, -2.38399 }, {115.05, -2.25599 }, {115.09, -2.00000 }, {115.15, -1.74400 }, {115.20, -1.48800 }, {115.25, -1.23200 }, {115.30, -0.975999 }, {115.34, -0.719999 }, {115.40, -0.464000 }, {115.45, -0.207999 }, {115.50, -0.207999 }, {115.55, 4.800009E-002 }, {115.59, 4.800009E-002 }, {115.65, 4.800009E-002 }, {115.70, 4.800009E-002 }, {115.75, -8.000003E-002 }, {115.80, 4.800009E-002 }, {115.84, -8.000003E-002 }, {115.90, -0.207999 }, {115.95, -0.464000 }, {116.00, -0.719999 }, {116.05, -0.847999 }, {116.09, -0.975999 }, {116.15, -1.10400 }, {116.20, -1.36000 }, {116.25, -1.23200 }, {116.30, -1.23200 }, {116.34, -1.23200 }, {116.40, -1.10400 }, {116.45, -1.10400 }, {116.50, -1.23200 }, {116.55, -1.10400 }, {116.59, -1.10400 }, {116.65, -1.23200 }, {116.70, -1.23200 }, {116.75, -1.36000 }, {116.80, -1.10400 }, {116.84, -0.847999 }, {116.90, -0.847999 }, {116.95, -1.10400 }, {117.00, -1.23200 }, {117.05, -1.36000 }, {117.09, -1.36000 }, {117.15, -1.23200 }, {117.20, -1.10400 }, {117.25, -1.10400 }, {117.30, -0.975999 }, {117.34, -0.847999 }, {117.40, -0.591999 }, {117.45, -0.719999 }, {117.50, -0.719999 }, {117.55, -0.591999 }, {117.59, -0.719999 }, {117.65, -0.719999 }, {117.70, -0.719999 }, {117.75, -0.719999 }, {117.80, -0.591999 }, {117.84, -0.591999 }, {117.90, -0.591999 }, {117.95, -0.464000 }, {118.00, -0.464000 }, {118.05, -0.207999 }, {118.09, -8.000003E-002 }, {118.15, 4.800009E-002 }, {118.20, -8.000003E-002 }, {118.25, -8.000003E-002 }, {118.30, -8.000003E-002 }, {118.34, -8.000003E-002 }, {118.40, -8.000003E-002 }, {118.45, -8.000003E-002 }, {118.50, -8.000003E-002 }, {118.55, 4.800009E-002 }, {118.59, 4.800009E-002 }, {118.65, 4.800009E-002 }, {118.70, 4.800009E-002 }, {118.75, 4.800009E-002 }, {118.80, 4.800009E-002 }, {118.84, 0.176000 }, {118.90, 0.176000 }, {118.95, 0.176000 }, {119.00, 0.176000 }, {119.05, -8.000003E-002 }, {119.09, -0.207999 }, {119.15, -0.207999 }, {119.20, -0.207999 }, {119.25, -8.000003E-002 }, {119.30, -8.000003E-002 }, {119.34, 4.800009E-002 }, {119.40, 0.303999 }, {119.45, 0.559999 }, {119.50, 0.815999 }, {119.55, 1.07200 }, {119.59, 1.32800 }, {119.65, 1.58400 }, {119.70, 1.58400 }, {119.75, 1.84000 }, {119.80, 2.09600 }, {119.84, 2.35199 }, {119.90, 2.48000 }, {119.95, 2.73600 }, {120.00, 2.99200 }, {120.05, 3.24800 }, {120.09, 3.24800 }, {120.15, 3.24800 }, {120.20, 3.12000 }, {120.25, 2.99200 }, {120.30, 2.73600 }, {120.34, 2.60800 }, {120.40, 2.60800 }, {120.45, 2.73600 }, {120.50, 2.73600 }, {120.55, 2.99200 }, {120.59, 3.12000 }, {120.65, 3.24800 }, {120.70, 3.24800 }, {120.75, 3.24800 }, {120.80, 3.12000 }, {120.84, 3.12000 }, {120.90, 2.86399 }, {120.95, 2.86399 }, {121.00, 2.73600 }, {121.05, 2.60800 }, {121.09, 2.48000 }, {121.15, 2.60800 }, {121.20, 2.60800 }, {121.25, 2.60800 }, {121.30, 2.86399 }, {121.34, 2.86399 }, {121.40, 2.99200 }, {121.45, 2.86399 }, {121.50, 2.99200 }, {121.55, 2.99200 }, {121.59, 2.86399 }, {121.65, 2.86399 }, {121.70, 2.86399 }, {121.75, 2.86399 }, {121.80, 2.99200 }, {121.84, 3.12000 }, {121.90, 3.37599 }, {121.95, 3.50400 }, {122.00, 3.63200 }, {122.05, 3.50400 }, {122.09, 3.50400 }, {122.15, 3.50400 }, {122.20, 3.50400 }, {122.25, 3.50400 }, {122.30, 3.50400 }, {122.34, 3.37599 }, {122.40, 3.24800 }, {122.45, 3.24800 }, {122.50, 3.12000 }, {122.55, 3.12000 }, {122.59, 3.24800 }, {122.65, 3.37599 }, {122.70, 3.37599 }, {122.75, 3.50400 }, {122.80, 3.75999 }, {122.84, 4.01600 }, {122.90, 4.27200 }, {122.95, 4.65599 }, {123.00, 4.65599 }, {123.05, 4.78399 }, {123.09, 5.04000 }, {123.15, 5.29600 }, {123.20, 5.55199 }, {123.25, 5.80799 }, {123.30, 5.80799 }, {123.34, 5.80799 }, {123.40, 5.93599 }, {123.45, 6.06400 }, {123.50, 6.19200 }, {123.55, 6.06400 }, {123.59, 5.93599 }, {123.65, 6.19200 }, {123.70, 6.57599 }, {123.75, 6.83199 }, {123.80, 6.57599 }, {123.84, 6.44800 }, {123.90, 6.32000 }, {123.95, 6.32000 }, {124.00, 6.32000 }, {124.05, 6.32000 }, {124.09, 6.19200 }, {124.15, 6.32000 }, {124.20, 6.19200 }, {124.25, 6.32000 }, {124.30, 6.19200 }, {124.34, 6.06400 }, {124.40, 5.93599 }, {124.45, 5.80799 }, {124.50, 5.42400 }, {124.55, 4.78399 }, {124.59, 4.27200 }, {124.65, 4.27200 }, {124.70, 4.40000 }, {124.75, 4.52799 }, {124.80, 4.14400 }, {124.84, 3.75999 }, {124.90, 3.50400 }, {124.95, 3.37599 }, {125.00, 3.37599 }, {125.05, 3.12000 }, {125.09, 2.48000 }, {125.15, 1.96800 }, {125.20, 1.58400 }, {125.25, 1.07200 }, {125.30, 0.815999 }, {125.34, 0.431999 }, {125.40, 0.176000 }, {125.45, -8.000003E-002 }, {125.50, -0.207999 }, {125.55, -0.719999 }, {125.59, -1.61600 }, {125.65, -2.38399 }, {125.70, -3.15200 }, {125.75, -4.04800 }, {125.80, -4.94400 }, {125.84, -5.58399 }, {125.90, -5.96800 }, {125.95, -6.35200 }, {126.00, -6.60799 }, {126.05, -6.86399 }, {126.09, -7.88799 }, {126.15, -8.91200 }, {126.20, -9.67999 }, {126.25, -9.80800 }, {126.30, -10.1920 }, {126.34, -10.8320 }, {126.40, -11.6000 }, {126.45, -12.6240 }, {126.50, -13.6480 }, {126.55, -15.1839 }, {126.59, -17.7440 }, {126.65, -19.6640 }, {126.70, -21.3279 }, {126.75, -22.6080 }, {126.80, -23.8880 }, {126.84, -24.9119 }, {126.90, -25.8080 }, {126.95, -26.4480 }, {127.00, -26.9600 }, {127.05, -27.0880 }, {127.09, -27.6000 }, {127.15, -28.7519 }, {127.20, -29.6480 }, {127.25, -30.2880 }, {127.30, -31.3120 }, {127.34, -32.3359 }, {127.40, -32.8479 }, {127.45, -33.6160 }, {127.50, -34.6400 }, {127.55, -36.1760 }, {127.59, -37.8400 }, {127.65, -39.3759 }, {127.70, -40.6559 }, {127.75, -41.9360 }, {127.80, -42.0640 }, {127.84, -42.1920 }, {127.90, -42.0640 }, {127.95, -42.1920 }, {128.00, -42.4480 }, {128.05, -42.5760 }, {128.09, -42.7040 }, {128.15, -42.8320 }, {128.19, -43.0880 }, {128.25, -43.6000 }, {128.30, -44.3680 }, {128.34, -45.0080 }, {128.40, -45.6480 }, {128.44, -45.9040 }, {128.50, -46.0319 }, {128.55, -46.0319 }, {128.59, -46.2879 }, {128.65, -46.7999 }, {128.69, -47.1839 }, {128.75, -47.5679 }, {128.80, -47.6959 }, {128.84, -47.9519 }, {128.90, -47.8239 }, {128.94, -47.6959 }, {129.00, -47.4399 }, {129.05, -47.1839 }, {129.09, -46.9279 }, {129.15, -46.6719 }, {129.19, -46.6719 }, {129.25, -46.7999 }, {129.30, -46.5439 }, {129.34, -46.4159 }, {129.40, -46.2879 }, {129.44, -45.7760 }, {129.50, -45.3920 }, {129.55, -45.0080 }, {129.59, -44.2400 }, {129.65, -43.9840 }, {129.69, -43.4720 }, {129.75, -42.9600 }, {129.80, -42.7040 }, {129.84, -42.3200 }, {129.90, -42.0640 }, {129.94, -41.5520 }, {130.00, -40.7839 }}

How can I reduce a non-linear trend of some data series if there are parts of "no data", represented by the value 99999? For example:

{{124.55,368.632},
 {124.6,281.976},
 {124.65,200.952},
 {124.7,91.384},
 {124.75,-60.424},
{124.8,-282.504},
 {124.85,-541.448},
 {124.9,-378.76},
 {124.95,99999},
 {125,99999},
{125.05,99999},
 {125.1,99999},
 {125.15,99999},
 {125.2,99999},
 {125.25,99999},
 {125.3,99999},
{125.35,265.46},
 {125.4,376.75},
 {125.45,462.54},...,{178.95,284.46}}

Normally, I am successful reducing the non-linear trend of the data via

lm = LinearModelFit[data, {a, a^2, a^3, a^4, a^5},a];
Do[aha = Last[Take[data, {m, m}]]; y = Last[aha]; 
  x = First[aha]; new[m] = y - lm[x], {m, idim}];

but have no idea how to do the trend-reduction between those data gaps (i.e., outside of the regions with data = 99999). The position of those regions is not constant.

Thanks a lot for each hint, Harald

P.S.: After the reduction is performed, the position of the "no data"-values should be the same as before

How can I reduce a non-linear trend of some data series if there are parts of "no data", represented by the value 99999? For example:

data={{124.55,368.632}, {124.6,281.976}, {124.65,200.952}, {124.7,91.384}, {124.75,-60.424},
{124.8,-282.504}, {124.85,-541.448}, {124.9,-378.76}, {124.95,99999}, {125,99999},
{125.05,99999}, {125.1,99999}, {125.15,99999}, {125.2,99999}, {125.25,99999}, {125.3,99999},
{125.35,265.46}, {125.4,376.75}, {125.45,462.54},...,{178.95,284.46}}

Normally, I am successful in reducing the non-linear trend of the data via

lm = LinearModelFit[data, {a, a^2, a^3, a^4, a^5},a];
Do[aha = Last[Take[data, {m, m}]]; y = Last[aha]; 
  x = First[aha]; new[m] = y - lm[x], {m, idim}];

but have no idea how to do the trend-reduction between those data gaps (i.e., outside of the regions with data = 99999). The position of those regions is not constant. After the reduction is performed, the position of the "no data"-values should be the same as before