How assess trend for time-series as a numeric metric in R?
Here is an example of data set converted into time-series object.
I'd like to find numeric metric 'x' that allows to identify type of trend.
Let say, x > 0 - "Rising Trend", x < 0 - "Falling Trend". The data has less than 2 seasons. Please, share your practical experience. Thanks.
# 1. Data set
df_data <- data.frame(
year = c(2000:2017),
count = c(3, 2, 1, 3, 17, 18, 59, 93, 144, 266, 263, 401, 802, 1263, 2366, 4170, 2617, 2382))
# 2. Time-series
ts_data <- ts(df_data$count, start = min(df_data$year), end = max(df_data$year), frequency = 1)
# 3. Plot
plot.ts(ts_data)
# 4. How identify up & down trend as a numeric metric?
r time-series trend
asked Nov 14 '18 at 19:51
andriiandrii
8931013
add a comment |
Here is an example of data set converted into time-series object.
I'd like to find numeric metric 'x' that allows to identify type of trend.
Let say, x > 0 - "Rising Trend", x < 0 - "Falling Trend". The data has less than 2 seasons. Please, share your practical experience. Thanks.
# 1. Data set
df_data <- data.frame(
year = c(2000:2017),
count = c(3, 2, 1, 3, 17, 18, 59, 93, 144, 266, 263, 401, 802, 1263, 2366, 4170, 2617, 2382))
# 2. Time-series
ts_data <- ts(df_data$count, start = min(df_data$year), end = max(df_data$year), frequency = 1)
# 3. Plot
plot.ts(ts_data)
# 4. How identify up & down trend as a numeric metric?
r time-series trend
asked Nov 14 '18 at 19:51
andriiandrii
8931013
add a comment |
Here is an example of data set converted into time-series object.
I'd like to find numeric metric 'x' that allows to identify type of trend.
Let say, x > 0 - "Rising Trend", x < 0 - "Falling Trend". The data has less than 2 seasons. Please, share your practical experience. Thanks.
# 1. Data set
df_data <- data.frame(
year = c(2000:2017),
count = c(3, 2, 1, 3, 17, 18, 59, 93, 144, 266, 263, 401, 802, 1263, 2366, 4170, 2617, 2382))
# 2. Time-series
ts_data <- ts(df_data$count, start = min(df_data$year), end = max(df_data$year), frequency = 1)
# 3. Plot
plot.ts(ts_data)
# 4. How identify up & down trend as a numeric metric?
r time-series trend
asked Nov 14 '18 at 19:51
andriiandrii
8931013
Here is an example of data set converted into time-series object.
I'd like to find numeric metric 'x' that allows to identify type of trend.
Let say, x > 0 - "Rising Trend", x < 0 - "Falling Trend". The data has less than 2 seasons. Please, share your practical experience. Thanks.
# 1. Data set
df_data <- data.frame(
year = c(2000:2017),
count = c(3, 2, 1, 3, 17, 18, 59, 93, 144, 266, 263, 401, 802, 1263, 2366, 4170, 2617, 2382))
# 2. Time-series
ts_data <- ts(df_data$count, start = min(df_data$year), end = max(df_data$year), frequency = 1)
# 3. Plot
plot.ts(ts_data)
# 4. How identify up & down trend as a numeric metric?
r time-series trend
r time-series trend
asked Nov 14 '18 at 19:51
andriiandrii
8931013
asked Nov 14 '18 at 19:51
andriiandrii
8931013
edited Nov 14 '18 at 20:08
andrii
asked Nov 14 '18 at 19:51
andriiandrii
8931013
asked Nov 14 '18 at 19:51
andriiandrii
8931013
asked Nov 14 '18 at 19:51
andriiandrii
8931013
8931013
add a comment |
add a comment |
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